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newestdoc

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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'Instruction'})

This happened while the csv dataset builder was generating data using

zip://Datasets/ERS_genai_1707401135.csv::/tmp/hf-datasets-cache/medium/datasets/86530492458941-config-parquet-and-info-Kushala-newestdoc-544d4269/downloads/02cd039ca67a44713260374def9338a24a7523316796e2122fb928fedd74fe94

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Response: string
              Instruction: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 500
              to
              {'Response': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1396, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1045, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1884, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2015, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'Instruction'})
              
              This happened while the csv dataset builder was generating data using
              
              zip://Datasets/ERS_genai_1707401135.csv::/tmp/hf-datasets-cache/medium/datasets/86530492458941-config-parquet-and-info-Kushala-newestdoc-544d4269/downloads/02cd039ca67a44713260374def9338a24a7523316796e2122fb928fedd74fe94
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Response
string
AION: “SWITCH ON AI”
Industry Challenges & Solution using AION Challenges HCL AION Advantage Dev elopment of ML Models takes long time & need specialized skill setEmpower people in organization whether Technical (Working in code) or Business (Low code/No code) to create ML Models Data needed for building ML Models is not centralized and is available in varied data formats & platformsHooks to integrate with varied enterprise data sources Handle data cleansing, data quality issues, data outlier issues Handle multiple data types and unstructured data Data scientists do not have deep domain understanding & Domain experts do not understand Machine LearningAION helps citizen data scientists develop ML Models. Reduces Repetitive work needed by data scientists in developing models Saves precious data scientist e fo rt by automating low end work ML Model & Data might drift with time, resulting in incorrect insights & predictionsModel monitoring support and drift analysis for input/output data & Model predictions ML Models are black box & give no explanation on predictionsAION provides detailed explanations on reasons for prediction Code Generated by AI Lifecycle Mgmt. Platform is not reusable across PlatformsMLaC feature generates Platform independent Python code & containers that can be consumed outside AION as wellInput AIONOverview Organizations today are targeting to promote democratization of Machine learning & AI, this will unlock immense potential that is still untapped as most of the domain experts are not capable of building ML models. AION will enable domain experts (Also known as Citizen Data Scientists) build ML models to derive useful insight from raw data & help resolve business problems. AION is an AI lifecycle management platform for applying machine learning to real-world problems. AION encompasses the
complete pipeline from raw dataset ingestion to deployable machine learning model with low-code/no -code approach. AION Includes the following sub-processes: •Data exploration, insights generation and transformation (Data Engineering) •Machine learning, deep learning and artificial intelligence training (Algorithms & Models) •Prediction interpretation/explanation, model testing and uncertainty quantification (XAI / ML Test / UQ) •Model deployment, model observation and model operations (MLOps) Output Model MLaC x4 x59 x54 y n y n Explanations / Uncertainty
AION Business Benefits Productivity Improvement of Data Scientists in ML Model development timeML models helping in Operational effciencyWider analytics adaptability across organization helping in providing more insights INGESTOR Data Ingestion Hooks to consume data from disparate sourcesAION Components EXPLORER Exploratory Data Analysis Visual exploratory data analysis to derive descriptive insightsTRANSFORMER Data Processing Data cleanup & preparation to improve data qualitySELECTOR Feature Selection Identification of relevant features based on correlation & importance LEARNER Model Training Hyper Parameter Tuning Identify best algorithm & parameters for highest scorePUBLISHER Model Publishing Flexible ML Model deployment options for varied environmentsPREDICTOR Inference Service ML Model Serving & inference services EXPLAINER Explainable AI Explanation & Uncertainty quantification of the predictionTESTER Model Testing Flexible ML Model deployment options for varied environmentsCONVERTOR Model Conversion for Edge Device Convert ML Models to edge & hyper - scaler platformsOBSERVER Model Monitoring Identification of relevant features based on correlation & importance CODER Machine Learning as Code Automatic generation of Python code for ML pipeline components PIPELINE VISUALIZER Exploratory Data Analysis Performance Visualization Visualize all stages of the pipeline AION Visualizer
AION Differentiators Integrate with any digital platform and provide analytics as a service ML as a code (MLaC) available for expert data scientists & easier maintenanceModel & Prediction ExplainabilitySingle platform providing services to convert raw data into insights & value Easy integration with diferent data sources and hyperscalers
www.hcltech.com HCL Technologies (HCL) empowers global enterprises with technology for the next decade today. HCL’s Mode 1-2-3 strategy, through its deep -domain industry expertise, customer -centricity and entrepreneurial culture of ideapreneurship enables businesses to transform into next -gen enterprises. HCL s its services and products through three lines of business - IT and Business Services (ITBS), Engineering and R&D Services (ERS), and Products & Platforms (P&P). ITBS enables global enterprises to transform their businesses through o in areas of Applications, Infrastructure, Digital Process solutions in all aspects of product development and platform engineering while under P&P. HCL provides modernized software products to global clients for their technology and industry specific requirements. Through its cutting -edge co-innovation labs, global delivery capabilities, and broad global network, HCL delivers holistic services in various industry verticals, categorized under Financial Services, Manufacturing, Technology & Services, Telecom & Media, Retail & CPG, Life Sciences, and Healthcare and Public Services. As a leading global technology company, HCL takes pride in its diversity, social responsibility, sustainability, and education initiatives. As of 12 months ending on December 31, 2021, HCL has a consolidated revenue of US $ 11.18 billion and its 197,777 ideapreneurs operate out of 52 countries. For more information, visit www.hcltech.com Network Quality of Service (QoS) Classification Complaint Identification for Medical DevicesA leading telecom service provider wanted to introduce QoS analytics capabilities in a device management platform that they were using from HCL using HCL AION, a solution to provide Descriptive and Predictive Analytics insights for the CPE devices was developed. The Descriptive Analytics included
dashboards for QoS Analysis, Degraded QoS and Statistical insights. Predictive Analytics included quality -based traffc patterns, forecasts of error rates, noise and signal strengths. Customer Order ForecastingA leading telecom service provider wanted to automate order volume and trend monitoring (which was being monitored manually). No telemetry was defined for order volume variation. AION was introduced for AI/ML based forecasting to help in defining telemetry for order volume variation. A time series forecasting model was developed that was trained automatically every 24 hours (or as per configured interval) to forecast volumes for the next period (1 hour or configured interval).The problem was to identify cases of medical device complaints given a set of device services report records using unsupervised and supervised techniques. The complaint data was passed through AION pipeline where data profiling and feature selection were performed. Constant features were removed, and low variance features were handled. Features with empty rows were imputed appropriately. Supervised classification and unsupervised clustering was performed as two diferent approaches to categorize complaints.Proof Points
Copyright © 2021 HCL Technologies Limited | www.hcltech.comAION –Switch ON AI Roadmap Navin Saini
FY24AION v4.0 Edge ML & Federated ML ✓Distributed Learning for Faster Training of ML Models ✓Federated Learning to address issues like data privacy, data security & access rights ✓Building ML Models for devices with resource constraints using TinyML ✓Security for Edge Models ✓CI/CD Pipeline leversFY23AION v3.0 MLOps & Hyperscaler Integration Enabling Model deployments in Production ✓Feature Store ✓Integration with CI/CD pipeline ✓Data Quality check ✓Efficient & light weight Containerization ✓Incremental & Reinforcement Learning ✓Platform Governance (Roles)FY22AION v2.0 ML Test, Explainable AI & MLaC Covering of features Beyond AutoML ✓Model Monitoring, ✓Explainable AI, ✓Model Confidence score (Uncertainty Quantification), ✓Model Benchmarking ✓ML as a Code (MLaC)Product Roadmap Of AION AutoML & Exploratory Data Analytics FY21 Implement Core AutoML features covering all the data analytics pipeline stages of any AutoML solution like Model Building, selection, Hyperparameter tuning. Data Pre -Processing, Model mgmt.AION v1.0
3|Copyright © 2021 HCL Technologies Limited | www.hcltech.comPRODUCT ROADMAP OF AION V 1.0 (RELEASED)V 1.2 (RELEASED)V 1.5 (RELEASED)V 1.7 (RELEASED)V 2.0 (RELEASED) Dec ‘20 June ‘21 Sept ‘21 Dec ’21 Mar ‘22Core AutoML (Structured Data) Implemented Core AutoML features covering all the data analytics pipeline stages of any AutoML solutionAutoML+ (Unstructured Data) Enrichment of core features by adding capabilities related to unstructured data and increase the breadth of offeringExtended Core (Production Focus) Addition of features to help in productionization of Analytics models such as MLTest, MLOps & Hyperscaler to differentiate from competitionAutoML++ (Feature Hardening) Increasing depth of our offering by hardening the features . Introducing the functionality related to better training & learning experienceModular Core Comprehensive release with advanced features like Machine Learning as a Code, Integration with GCP and Optimized Ensemble algorithms Core AutoML PipelineImage Simulation & Labeling Object annotation & detection Edge Models (ONNX) Remote Training of modelsML Testing ML Ops (MLFlow integration) Hyperscaler Integration Containerization (Docker) Drift Analysis Edge Models (TensorRT)KubeFlow Integration TinyML for lightweight & low power edge devices Optimization of Algorithm & Pre-Processing stages Adverserial & Perturbation TestingMLaC – ML as a Code (Code, Container, Config) Document Similarity New Ensemble algorithm support ( CATBoost & Light GBM) Kubeflow Integration Optimized Edge Conversion Secure REST API
4|Copyright © 2021 HCL Technologies Limited | www.hcltech.comMARKET COMPETITION Tool / Framework / Vendor Classification Regression Time series Clustering Recommender System Survival Analysis Anomaly Detection Constraint Optimization Bayesian Optimization Genetic Programming Ensemble Construction Tree Parzen Estimator Neural Architectural search Grid Search Random Search Data Pre - processing Feature Selection Similarity Detection Drift Handling Cross Validation Data Balancing Tibco Software✓✓✓✓✓✓✓✓✓ ✓ ✓✓✓ ✓ RapidMiner ✓✓✓✓✓✓✓ ✓ ✓ ✓✓✓✓✓ ✓✓ IBM ✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓✓ Alteryx ✓✓✓✓✓✓✓ ✓ ✓ ✓✓✓✓ ✓ Databricks ✓✓✓✓✓✓✓ ✓ ✓✓ ✓✓✓✓ ✓ Deep Cognition AI✓✓✓ ✓ ✓✓✓ ✓ Dataiku ✓✓✓✓ ✓✓✓✓✓✓✓ Data Robot ✓✓✓✓ ✓✓ ✓✓✓✓✓ H2O ✓✓✓✓✓✓✓ ✓ ✓✓✓ ✓✓ AI.ON (HCL ERS)✓✓✓✓✓✓✓ ✓✓✓ ✓✓✓✓✓✓✓✓✓ML Algorithm Type Hyper Parameter Tuning & Optimization Miscellaneous
$9.9 BILLION | 150,000+ IDEAPRENEURS | 50 COUNTRIES
6|Copyright © 2021 HCL Technologies Limited | www.hcltech.comINDUSTRY CHALLENGES & SOLUTION USING AION
7|Copyright © 2021 HCL Technologies Limited | www.hcltech.comSOLUTION PROVIDED BY AION Data pre -processing •Handle data cleansing, data quality issues, data outlier issues •Handle multiple data types and unstructured data •Hooks for integration with disparate data sources Feature Selection •Identifying features from the data •Feature Correlation and reduction of features if needed Model Training • Ability to interpret model function and try out multiple models • Ability to optimize model parameters and fit the model with required scoring criteria • Handle overfitting of data and handle varied class of data Model Testing and Explainable AI • Provide model testing capabilities to baseline models, assess performance and confidence • Generate multi -dimensional KPIs and explanations of predictions ML Operations •Provide all common deployment options for ease of integration with third party applications •Support for open standards of edge deployment for hardware agnostic deployment Monitoring •Detect and notify data drift •Ability to configure and detect prediction drift
AION Product datasheet AI lifecycle management platform to assist data scientists & business users create, experiment, productize & Improve ML & LLM models to derive insights using low -code/no -code approach & enabling citizen data scientists(CDS) in an organization. Key Highlights •One platform from raw data to insights •One platform for all users ranging from domain engineers (No AI or code knowledge) to expert data scientists •Build once and deploy anywhere (including edge) •Easy integration of AION with customer existing digital platforms •Open for Research based collaboration in development of ML solution •AI as code •Generative AI Capabilities for Finetuning & Embeddings Generation using OpenAi & LLaMA2 Benefits •Continuous automation •Productivity Improvement •Improves operational efficiency and throughput •Helps in deskillingSalient Features •Intelligence for all covering entire ML Pipeline - AION is for everyone, from AI builders (Expert Data Scientists) to AI consumers (Domain users) •Generative AI Capabilities - Finetuning(Partial & Full) & Embeddings generation using online & Offline LLM Models like OpenAI & LLaMA2 to solve problems like QnA , Text summarization & Data Labeling. •Ecosystem of algorithms - AION supports all state -of-the -art algorithms including ensemble. It explores multiple algorithms with ideal hyperparameters resulting in an accurate system. •Hyperscaler Integration - AION can integrate with HyperScalers like AWS, Azure & GCP providing security, reliability & scalability to the ML model. •MLaC & MLOps - Automatic generation of Python code(& containers) for all ML Pipeline stages. Container orchestration using Kubeflow. •Varied deployment option - As Python Package, Docker & Service Endpoint, Model on Edge devices (ONNX & TFLite format), Model on Hyperscalers – Amazon Sagemaker •Benchmarking of AI & LLM Models - AION supports benchmarking of LLM & ML Models generated within or outside of AION •Model Observability - Input (Data Drift) &
•Model Observability - Input (Data Drift) & output(Prediction Drift) drift analysis for timely alerts •Trusted AI - Data Bias, Fairness, Transparency, Robustness & Explainability
Technical Requirements Third -Party Tools Component Requirement Processor 64 bit processor; Intel corei3, A100 GPU(for fine tuning) RAM 16GB RAM, 40GB (For Fine tuning) Operating SystemAny 64 bit Windows/ Linux HDD Free Space100GB min (preferred 500 GB) Java JDK 8 Other software Pre-requisitesGUI - Google ChromeHyperscaler Integration Data Ingestion Integration MLOPs Integration Capability Integration AION Solution Components Engines EXPLAINER – Explainable AI Explanation & Uncertainty quantification of the prediction TESTER – Model Testing Benchmarking & Testing of ML Models CONVERTOR – Model Conversion for Edge Device Convert ML Models to edge & hyper- scaler platforms CODER – Machine Learning as Code Automatic generation of Python code for ML pipeline components Benchmarking Benchmarking of LLM Models for safeguarding against performance deterioration PUBLISHER – Model Publishing Flexible ML Model deployment options for varied environmentsPREDICTOR – Inference Service ML Model Serving & inference services OBSERVER – Model Monitoring Model Monitoring for input & output drift of data or predictions INGESTOR & EXPLORER – Data Ingestion & Analysis Hooks to consume data from disparate sources & visually explore & analyze the data for descriptive insightsTRANSFORMER & SELECTOR – Data Processing & Feature Selection Data quality improvement & identification of important features based on correlationLEARNER – Model Training Hyper Parameter Tuning Identify best algorithm & parameters for highest scoreLLM Fine -tuning Partial (PEFT) & Full finetuning with configurable parameters for offline LLM Models on AWS & GCP Run + Design Time EnginesDesign Time Engines
HCLTech is a global technology company, home to 222,900+ people across 60 countries, delivering industry -leading capabilities centered around digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending March 2023 totaled $12.6 billion. To learn how we can supercharge progress for you, visit hcltech.com.
hcltech.com CUSTOMERS CHALLENGES Development of ML & Private LLM Models takes long time & need specialized skill set Data needed for building ML Models is not centralized and is available in varied data formats & platforms Data scientists do not have deep domain understanding & Domain experts do not understand Machine Learning Unable to Identify input & output drift for data for models in production HCL’s AION KEY OFFERINGS AION makes it easier for Citizen data scientists to develop ML & LLM models. Provide various mechanisms & connectors to consume data from varied sources Generative AI is offered by AION as a capability which is not part of most of the AutoML solutions in market like OpenAI & LLaMA2 Automatic Identification of input & output drift for data & ML Models BUSINESS BENEFITS Productivity Improvement of Data Scientists in ML Model development time ML models helping in Operational efficiency Wider analytics knowledge across organization helping in providing more insightsDIFFERENTIATORS Integrate with any digital platform and provide analytics as a service Single platform providing services to convert raw data into insights & value Build once deploy anywhere Easy integration with different data sources and hyperscalers ML as code(MLaC) available for expert data scientists & easier maintenance Generative AI (LLaMA2 & OpenAI) Positioning statement HCL has taken a lead in the field of AI/ML by coming up with its own AI lifecycle management platform i.e. AION. AION can assist expert data scientists or domain experts without AI or code knowledge to build ML models & derived useful insights from raw data.Expertise on AI/ML HCL continues to keep pace with the market dynamics through continued investments for technology and service capability development. HCL has a strong focus on driving large-scale AI/ML transformation, specifically for the large enterprise COMPETITIVE POSITIONING AION OFFERING World Class Delivery Organization
World Class Delivery Organization HCL has world class delivery infrastructure and processes backed by strong management and governance teams. AUDIENCE CDO, CTO, CIO VP & Director Digital, Products, AppsELEVATOR PITCH: AION is an AI lifecycle management platform to assist data scientists and business users create, experiment, productize and i mprove ML models using classic & Generative AI to derive insights using low code/no- code approach and enabling “citizen data scientists” in an organization.
hcltech.com AEROAREAS WHERE AION CAN PROVIDE SOLUTION OBJECTION HANDLING QUESTIONS 1.There are many AI/ML solutions in the market. Why should we choose AION over others? AION supports all the major features & capabilities supported by major players in market. Some of the differentiators that we would like to highlight are: Easy Integration with existing customer digital platforms Customization support as per customer needs Comprehensive deployment options (incl. edge devices) Feature set covering entire AI/ML pipeline & not just model building. AI available as code for expert data scientists & easier maintenance Includes Generative AI (Online-OpenAi & Offline-LLaMA 2) 2.Which specific domain or vertical solutions does AION serve? AION is domain agnostic as it is applicable to all the domains. It can be used across various industries like Industrial, Aero, semi -conductors, Medical, Auto, consumer Electronics etc. It can help in predicting failure of equipment across various domains such as Industrial, Aero, medical etc. It can also help in enhancing customer experience with analytics in different domains such as Medical, Auto, Consumer Electronics etc . In this way, AION serves various domains. 3.How does HCL compare to other well -known Analytics solution provider? HCL applies proven expertise and pre-built assets to provide businesses with unmatched analytics and AI expertise. Pre-built assets include advanced laboratories for IoT, integrated Computer Vision + NLP, and Analytics + AI. Pre-built assets accelerate solutions which includes automated AI processing, tools and frameworks for AI/ML development, and domain specific solutions. HCL leverages its strategic partnerships with leading AI technologies and cloud paradigms to bring strategic value to clients. HCL’s Analytics and AI services help clients innovate their products and processes, and differentiate themselves from competitorsFailure prediction of equipment Operation optimization to reduce cost
Operation optimization to reduce cost Robotics: Image Classification Network Service Assurance Sales and Marketing Analytics Customer Experience Enhancements Self-organizing and self -healing network Clinical Decision Support System Proactive healthcare Connected product usage & quality analysis Yield control and asset optimization Quality early warning systems Field and warranty management Image Classification for driver assistance systems Predictive maintenance and vehicle health monitoring Insurance analytics Sales and marketing analytics Customer experience enhancement Optimize field support operations Predictive Maintenance Asset health monitoring dashboard Predictive maintenance alerts Last mile optimization of spare parts Sales and Marketing Analytics Customer Intelligence Engineering and Support operations optimization Product/Service Performance AnalysisINDUSTRIAL MEDICAL AUTO CONSUMER ELECTRONICSSEMI- CONDUCTORSNETWORK SYSTEMS ISV/ONLINE
hcltech.com HCLTech is a global technology company, home to 225,900+ people across 60 countries, delivering industry -leading capabilities centered around Digital, Engineering and Cloud powered by a broad portfolio of technology services and software. The company generated consolidated revenues of $12.8 billion over the 12 months ended March 2023. To learn how we can supercharge progress for you, visit hcltech.com. 1.Helps to identify solutions/capabilities which can be positioned in AI/ML & Generative AI spectrum 2.Understand opportunities to help the client with specific AI/ML areas 1.Identify how AI/ML & Generative AI( OpenAi & LLaMA2) investments can enhance revenue and services 1.Helps to align Classic & Generative AI to customer’s roadmap 2.Helps to identify investment or partnership opportunitiesSALES PROBING QUESTIONS TO CLIENTS DirectorWhich are your major AI/ML Transformation Pain points? CONTACT US : Navin Saini - navins@hcl.comHow can AI/ML Technologies bring new value to your customers? What is your AI roadmap?CDO, CTO, VP & General Managers
Copyright © 2022 HCL Technologies Limited | www.hcltech.comAI Lifecycle Management Platform Competitive AnalysisSwitch on AI
2 Copyright © 2022 HCL Technologies Limited | www.hcltech.com Competitor Analysis FeaturesAzure AutoMLAmazon Gluon Dataiku Google AutoML DataRobot H2O Data Pre -processing     Text Analytics       Feature Selection       Algorithms Supported    Neural Architecture Search        Model Testing        Explainable AI        Uncertainty Quantification        Model Conversion        Flexible Deployment     Model Monitoring       Hyper -scalar Integration         Not Applicable  Basic  Supported  Good  Extensive As per June 22
• • • • Insights & Impact Data Sources Data Ingestion Pre- ProcessingBuild ML Models Deploy ModelsPredictions Model MonitoringExperiment & Optimize Data & Feature EngineeringMachine Learning (Experimentation & Optimization)MLOps (Production & Operations) ML Model MLaC Explanations Python Package Edge REST APIBusiness UsersVisualization & Feature EngineeringDocker Drift Analysis Docker Expert Data Scientist Deployment Options Consumers
Problem Types14 Supported Algorithms56 EDA Features09 Large Language Models04 AION can handle more than 14 types of problem types including Classification, Regression, Topic Modelling & Survival analysis56+ algorithms supported including supervised & unsupervised learning. Ensemble & Deep LearningExploratory Data Analysis capabilities like statistical analysis, data distribution, correlation analysis, feature importance, data deep dive & bias Identification Fine Tuning of 10 variants of pre-trained models are supported on AWS and GCP configurations Feature Engineering Recipes07 Model Conversion Formats09 MLOps Integration08 Advanced Learning Techniques08 Feature selection & feature reduction techniquesVarious Edge formats (ONNX, TFLite), Hyperscalers & Python packagesSupports experimentation, code generation, GitHub integration, MLFlow tracking, registration, Kubernetes, model monitoringIncludes Federated Learning, Distributed Learning, Online Learning and Homomorphic Encryption
Fine Tuning & Benchmarking Foundation LLM User Data Fine Tuning with Hyperparameter Data Scientist Private LLM Fine-Tuned Large Language Model on User Data LLaMA2 -7B & LLaMA2 -13B Embeddings Generation Documents (PDF, Doc, Text) (Offline & Online LLM) Database
• • • • •
Customer Digital Platform Core Functionalities Feature SetPrediction API Response PROPOSITION 1 Provide AION as a part of digital platform offering . In this case, AION is being integrated with the existing digital platform . It is embedded as a component of the digital platform .PROPOSITION 2 Provide AION as a standalone platform In this case, AION is outside the existing digital platform . It can be called from the digital platform using APIs or web services . It can be used as Analytics as a service . AION in integration with digital platform AION as a standalone platformCustomer Digital Platform Core FunctionalitiesFeature SetAION Developed ML Models
MLaC generates code automatically based on ML Operations performed during various ML Lifecycle . Using MLaC, expert data scientists can have better control on experimentation, optimization & deployment of ML Models . MLaC has four unique components . Generate Container Automatically Build container with github actions for all the components . Compatible with Kubernetes & Kubeflow .Generate Code Automatically Generate Python code for each ML Pipeline like Data Engineering, Feature Engineering & Model Training etc.Model Monitoring Monitor the pipeline for performance degradation & replace alternate model based on accuracy Container Orchestration Stitch Pipeline containers in a ML pipeline to derive a meaningful outcome
This pipeline will enable Model developers & MLOps engineers in ML model deployment to production & monitoring . Automatic drift identification & triggering of necessary actions for keep pipeline relevant . Model MonitoringData IngestionData TransformerFeature EngineeringModel TrainingModel Serving Monitors model as per schedule of pipeline . If Drift is observed in new data, then entire pipeline will be triggered again . Ingestions of data as specified by AION at the time of model creation Transform the data as per the business needs of the ML ModelSuggestion of features based on statistical, or ML model Model Training, each algorithm will have a separate container . Champion model will be selected based on performance for servingMaintaine Registry of ML Models on MLFlow Model will be served by exposing an end point that can be consumed by any applicationModel Registry Kubeflow Pipeline
Hyper Parameter Tuning Algorithm based hyper parameters Grid Search Random Search Bayesian Genetic AlgorithmSampling SMOTE Over Sampling Tomelinks Under SamplingScoring Criteria Classification oAccuracy oPrecision oRecall oF1 score oROC AUC Regression oMAE (Mean Absolute Error) oMSE (Mean Squared Error) oRMSE (Root Mean Square E) oR2 (Statistical Measure ) Clustering oSilhouette Coefficient oCalinski -Harabasz Index oDavies -Bouldin Index Scoring Criteria Forecasting oRMSE oMAE Recommender oRMSE oMAE Association oSupport oConfidence oLiftOptional Configurations Search Optimization parameters: oK fold CV split percentage oTrain / Test percentage oIterations Number of clusters: auto or configurable Making false failures zero (FP, FN = 0) Top N recommendations
Traditional Approach New & Better Approach (Buy & Customize) •Buy source code for upfront value, cost optimization and reduced time to market •Customize code / platform using own resources or use SI services •Regular code updates & feature enhancements can be negotiated as part of deal 02Complete Ownership Organization has complete ownership of the platform & can define the roadmap as per organization priorities. Development of features can be taken care by customer or HCL resources. 03Easier Modifications As the changes in customer source code branch is not shared with anybody, customer can create their own prioritization on features & release cycle. 01Tailor Made Platform or solution is tailor made as per organization needs & need not be generic like one size fits all approach. 04Offers Scalability Scalability needs are as per organization requirements & can be aligned to hyperscaller or infrastructure choice of customer
Sweden based multinational clothing customer The problem was to identify cases of medical device complaints given a set of device services report records using unsupervised and supervised techniques. The complaint data was passed through AION pipeline where data profiling and feature selection were performed. Constant features were removed, and low variance features were handled. Features with empty rows were imputed appropriately. Supervised classification and unsupervised clustering was performed as two different approaches to categorize complaints. Major Japanese industrial customer Apart from basic AutoML capabilities, custome r appreciated the features like Uncertainty quantification (provides a confidence level of the model in predictions) & explainability(Provides the explanation behind the prediction). Model explainability is part of responsible AI & hence part of compliance in certain geographies.Dutch based multinational conglomerate customer Customer appreciated AION’s collaborative solution related to all the data science related work across organization. Centralised MLOps capability was area of keen interest & resulted in identification of areas of engagement with customer. MLac was another powerful feature that helped customer achieve the total control of ML models in production. US Based Chip Manufacturer Impressive AutoML based capability to save significant effort in ML Models using No -code/Low -code approach. AION is also able to automate ( & hence save significant repetitive & low-end work) done by expert data scientists. Created models for automatic categorization of defects related to infrastructure (False Failures) using log files. 03 02 0401
# AWS Models LoRA QLoRA 1 LLaMA-2 7B ✓ ✓ 2 LLaMA-2 7B Chat ✓ ✓ 3 Code LLaMA-2 7B ✓ ✓ 4 LLaMA-2 13B - ✓ 5 LLaMA-2 13B Chat - ✓ 6 Code LLaMA-2 13B - ✓Technique # GCP Models LoRA QLoRA Full Fine Tuning 1 LLaMA-2 7B ✓ ✓ ✓ 2 LLaMA-2 7B Chat ✓ ✓ ✓ 3 Code LLaMA-2 7B ✓ ✓ ✓ 4 Falcon 7B ✓ ✓ ✓ 5 LLaMA-2 13B ✓ ✓ ✓ 6 LLaMA-2 13B Chat ✓ ✓ ✓ 7 Code LLaMA-2 13B ✓ ✓ ✓ 8 Code LLaMA 34B - ✓ - 9 LLaMA-2 70B - ✓ - 10 Falcon 40B - ✓ -Technique
D R A F T V E R S I ON, H C L C O N FI D E NT I A L A N D I N T E R NA L P U R P OS E O N LY1Device Complaint Classification for a Medical OEM client BenefitsKey Differentiators Problem Statement Solution Approach•Automated machine learning pipeline that does data profiling, feature selection and model generation •Automated visualization of descriptive and predictive results •Automated deployment models made available either as a service or as a package Complaints data had numeric, categorical and text features like Hospital, Model, Serial No., Test Date, Instrument Inspection, Reason, Technician Note, Manual Exception Reasons, Manual Exception Comment Feature Selection: •Removed constant and low variance features •Features with empty rows imputed appropriately Performed supervised classification and unsupervised clustering as two different approaches to categorize complaintsIdentify cases of medical device complaints given a set of device service report records using unsupervised and supervised techniques Accuracy Improvements8%30%70% 40% Ease of DeploymentEase of IntegrationModel GenerationEfficiency Improvements Results Approach 1: Supervised Classification •Achieved accuracy ~100% in detecting complaints vs non -complaints Approach 2: Unsupervised Clustering •Achieved ~87% accuracy in clustering complaints vs non -complaints
D R A F T V E R S I ON, H C L C O N FI D E NT I A L A N D I N T E R NA L P U R P OS E O N LY2AI/ML based Order Forecasting for a Telecom Service Provider client Aggregate at hourly intervals Approach •Use AI/ML based forecasting to help in defining telemetry for order volume variation •Define AI/ML Model that will be trained automatically every 24 hours (or as per configured interval) •Forecast volumes for next period (1 hour or configured interval)Order Telemetry data Results •Time Series Forecasting using 4 months of historical data •Achieved next 24 hours order forecasting with 90% accuracy •Provided configurable option to forecasting for next x hours or next y daysProblem Statement •Order volume trend monitoring is manual •No telemetry defined for order volume variation Order Forecasted ResultsModelTrainTest Train and generate time series forecasting model
D R A F T V E R S I ON, H C L C O N FI D E NT I A L A N D I N T E R NA L P U R P OS E O N LY3 Detecting pump faults based on vibration analysis for an Industrial OEM client 1. Data Collection •Data for 84 secs were captured for each fault condition •Data was captured in 150+ files, each file containing 10000 raw data values 2. Nature of Data •Types of Fault data collected: •Inner Ring Race Fault •Outer Ring Race Fault •Seal Fault •Cavitation Fault •Good condition3. Solution Development •Following features were extracted from the vibration data from each file – Mean, Standard Deviation, Variance, Kurtosis, Skewness, Crest Factor, Minimum, Maximum and Sum •Normalization was done on features •Training and Test data were split in the 80%:20% ratio 4. Benefits •Model available for easy deployment: as a package or as a service •Prediction API available to categorize new data points~100MB of data collected 97% accuracy of fault detection achieved 5 categories of faults capturedFlexible deployable model Seal FaultOuter ring Race Fault Inner ring Race Fault
Copyright © 202 3 HCL Technologies Ltd. | Confidential 1 Key Features Flow Diagram Wiki/KM Error/Bug Database DB/CRMData Extraction NLP/NLUAssociation and recommendation Generative AI Resource planning Demand forecasting Problem resolutionTicket management Knowledge managementAPI Custom Library Plugin/extensions Dashboard/Web portal Classification Cluster AnalysisData Cleaning Data Mapping Feature Extraction Data Transformation Data Integration Text Mining Scoring Forecasting AI Chatbot Similar Ticket identification Smart Ticket Assignment Dynamic Visualization Bug Prioritization Ticket Volume Prediction Ticket Clustering Ticket classification Log Analysis Generative AI based use cases Productivity Customer Satisfaction Response time Collect relevant Historical data Mine critical information By Using AI/MLOptimize task, Improve process and productivity IAFS framework built on top of iTS (Intelligent Tech Support) that leverage AI/ML and Gen AI to enhance field support operations . It streamlines ticket resolution, reduce manual efforts, improve product support quality to boost field support team efficiency and productivity .
Q1 FY25ISE v1.2 Program Management Use Cases, Upstream and Downstream Connectors/Plugins Q4 FY24ISE v1.0 Dev and Test Use Cases, Upstream and Downstream Connectors/Plugins •Additional Development Use Cases using Offline (Meta Llama 2) and Online (Azure Open AI) LLMs: •Design Activities - High Level, Low Level and Database Design •Augmented Code Commits, Merge Conflict Resolution •Static Code Analysis •Additional Testing Use Cases using Offline and Online LLMs : •Test Case Standardization, Test Case and Script Maintenance •Test Data Generation •Augmented Bug Logging •Upstream Connector Integrations: SVN, BugZilla •Downstream Application Plugins: •IDE: Eclipse•Program Management Use Cases using Offline (Meta Llama 2) and Online (Azure Open AI) LLMs: •Requirement Gathering and Summarization •Functional Spec Creation •Feature Prioritization and Roadmap Creation •Feasibility and Risk Analysis •Project Level Tarige and Planning •Release Planning •Upstream Connector Integrations: JIRA •Downstream Application Plugins: •IDE: Visual Studio, JetBrains •Browser: MS Edge •Support for new Online LLMs: •Google Vertex AI PaLM •AWS Bedrock Titan
Q1 FY25ISE v3.2 Support Training Use Cases, Upstream and Downstream Connectors, Security Enhancements Q4 FY24iTS v3.1 Integration Pipeline strengthening and new online/offline GenAI use cases •Reinforcement Learning Pipeline for OpenAI •Reinforcement Learning Pipeline for Llama2 •Distributed Inference Server Integration using” •vLLM •TensorRT -LLM •Additional Use Cases using Offline (Meta Llama 2) and Online (Azure Open AI) LLMs: •Case Notes Documentation •Predictive Maintenance •Log Trend Analysis •iTS UI Revamp •Prompt Configuration •Prompt Testing and Integration •Enhancement s to Usecase creation modules•Additional Support Use Cases using Offline and Online LLMs : •Virutal Issue Simulation •Workload Distribution •Training Documentation Creation •Machine Generated Events Monitoring •Executable Script Generation for Runbook •Virtual Tutoring •Upstream Connector Integrations: SNOW, SFDC •Security : •Homomorphic encription •Inflight data encryption •Support for new Online LLMs: •Google Vertex AI PaLM •AWS Bedrock Titan*
Market Overview Field service management (FSM) is an advanced software solution designed to effectively manage various components to streamline field activities such as scheduling, vehicle tracking, inventory management, and customer po/r_t.ligaals. FSM remains at the fore front of innovation, providing businesses with the latest tools and features to optimize their field service operations. By adopting FSM, firms can benefit by maximizing operational efficiency and fostering consumer-led experiences. There is, there fore a growing need for customer-centric solutions, leading to an increased demand for field service solutions. The global field service management (FSM) market was USD 2.87 billion in 2020. Its market size is estimated to grow from USD 3.24 billion in 2021 to USD 8.06 billion by 2028, at a CAGR of 13.9%. The increasing popularity and market share of FSM can be a/t_t.ligaributed to cu/t_t.ligaing-edge technological improvements in the field.Intelligent Automation for Field Suppo/r_t.liga (IAFS) is a framework developed on top of iTS (Intelli Service) that enables be/t_t.ligaer field suppo/r_t.liga operations by providing suppo/r_t.liga insights, enabling process optimization and improving field workforce productivity. IAFS solution resolves ticket quickly by deploying AI/ML models to mine critical insights. The framework reduces the manual effo/r_t.ligas involved in ticket resolution, reducess turn-around time and improves suppo/r_t.liga quality for products.
Functional Architecture iTS Engine Advanced Machine learning & analytics engineAdministrative ConsoleVe/r_t.ligaical Specific Integrations Web Inte/r_f.ligaace Mobile Inte/r_f.ligaace Chat Inte/r_f.ligaace APIIAFS Solution Overview Presentation/Integration Layer Distributed Model/Storage Distributed/Scalable AI/ML StackAPI Meta Data Wiki / KM Error/Bug DatabaseEscalation/Compatibility Matrix/Known IssuesEnvironment DB /CRM/CSAT DBKnowledge A/r_t.ligaicles, Title, Summary, ResolutionBug Description, Product/Env/Config to bug mappingIssue Occurances – Interval wise, E-Com DataPre-requisites for escalation, KI – Product/ver/build wiseIssue – Product/ ver/build/config/ env wiseAnalytics ETLInput SourcesText MiningNLU/NLP Graph/OntologyAssociation & Recommendation. Optimization ModelTime-Series Forecasting ScoringClassification Cluster Analysis Contextual RelevanceSentiment Analysis Usage Analysis Entity ExtractionDerived Models Custom RulesCustom LibraryBrowser Plugin/ExtensionsWeb Po/r_t.ligaal/Dashboard Consumption VOIP/Ecom Data Sources
Functional Challenges Functional Benefits Slow response time for basic first-level issuesConversational AI agent automatically responds to customer enquiries and pe/r_f.ligaorm tasks Multiple field visits required todeploy suppo/r_t.ligaPa/r_t.ligas prediction enables seamlessidentification of pa/r_t.ligas and their need for replacement Assigning tickets manually to different agents can be error-proneSma/r_t.liga ticket assignment suggests thebest service agent to assign the ticket Similar/duplicate tickets, clu/t_t.ligaered,unorganized tracking of updates and requestSma/r_t.liga ticket classification Unstructured big data is difficult to analyzeData is structured on the basis of the identified pa/t_t.ligaerns of events, errors & messages in log files from devices & equipment Sca/t_t.ligaered knowledge across multiple sources leading to increased MTTRAI/ML based advanced suppo/r_t.liga data analytics framework helps in examiningvarious data sources
Differentiators AI/ML based advanced suppo/r_t.liga data analytics framework to optimize product and field suppo/r_t.liga operations IAFS is preloaded with product and field suppo/r_t.liga use cases for easy adoption Ability to automate remote repair actions and diagnostics process. Enables volume avoidance and self-help capabilities Ability to easily train and onboard conversational inte/r_f.ligaace and predictive use cases over existing suppo/r_t.liga platformOut-of-the-box integration with various enterprise channels and applications like Teams, mIRC etc. Benefits of Intelligent Automation for Field Suppo/r_t.liga Reduces MTTR by 28.4%Reduces trouble shooting time by up to 50%Enables deskilling Reduces solutionidentification time by 41%Improves CSAT and product experiencHelps retain knowledgebase avoiding knowledge gap
Proof Points Why HCLTech? HCLTech continues to keep pace with the market dynamics through continued investments intechnology to ensureservice capability development. HCLTech has a strong focus on driving large-scale AI/ML transformation, specifically for the large enterprise. HCLTech’s Engineering and R&D Services (ERS) empowers enterprises to improve time-to-profit, accelerate product development and maximize return on investment. Building on four decades of leadership in engineering services, we combine the technological depth and solution-driven approach to provide customers with comprehensive end-to-end solutions. HCLTech’s ERS offerings span the entire spectrum of digital engineering solutions and leverage more than 60 solution accelerators and next-generation technologies such as Cloud, IoT, AI, augmented reality, vi/r_t.ligaual reality (AR/VR), and autonomous vehicles. HCLTech has a world-class delivery infrastructure and processes backed by strong management and governance teams.IAFS helped a leading online solutions vendor to help reduce the initial investigation time by identifying the possible solutions and related issues for any given problem statement.This enabled theteam to achieve an overall 10% improvement in mean response time and a 5 – 8% improvement in the mean time to resolution.IAFS helped a leading antivirus vendor reduce the overall incoming tickets via chat and emails by 60% with the help of chatbots. With the help of chatbot implementation, there was a significant reduction in the number of repo/r_t.ligaed issues, which were repetitivein nature, and productivity was improved by 10%. Large enterprise IT suppo/r_t.liga teams used IAFS to help standardize their operations by leveraging its features in a vi/r_t.ligaually integrated mode with their existing toolsets.Overall, an improvement of 15% in MTTR and a 5-10% improvement in MRT has been observed with an 85% of coverage.
hcltech.com HCLTech is a global technology company, home to more than 223,400 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad po/r_t.ligafolio of technology services and products. We work with clients across all major ve/r_t.ligaicals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2023 totaled $12.8 billion. To learn how we can supercharge progress for you, visit hcltech.com.
• • • • • • • • • • • • • • IAFS framework is built on top of iTS (Intelligent Tech Support) that leverage AI/ML and Generative AI to enhance field support operations . It offers valuable insights, optimize processes, streamlines ticket resolution, reduce manual efforts, product support quality, and offers predictive modeling capabilities .
Other software Pre-requisites Data Extraction Classification Clustering Predictive AnalyticsSentiment AnalyticsGen AI Fine tuned LLM Text analysis Recommendation NLP WebMobile Chat API Knowledge Repository Data Lake Document Library Logs CRM
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4 • • • • • • • Similar Ticket Identification Identification of similar tickets based on context for easy reference of the historical tickets Self Service & Technical Support Question answering module from a given data sourceResolution Recommendation Given a query, identify the best resolution for the given contextIssue Summarization Summarization of technically complex and verbose tickets for easy understanding and assignationEscalation Identification Classifying an issue as escalated issue for reduced MTTR Tone and Sentiment Analysis Analysis of tone and sentiment based on user input Diagnostics Questionnaire Identifying the relevant questionnaires for a given issue to arrive at a solutionRelated Issue Identification Identification of the next issue based on the current and historical trend Knowledge Base Article Creation Dynamic generation and documentation of the solution used for issue resolution Ticket Routing Identifying the right resource for assignation of the given issueAvailable using ML & Generative AI Available using Generative AI only
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INTELLIGENT AUTOMATION for FIELD SUPPORT (IAFS)-MASTER LICENSE AGREEMENT BY DOWNLOADING, INSTALLING, COPYING, ACCESSING, CLICKING ON AN “ACCEPT” BUTTON, OR OTHERWISE USING THE PROGRAM, YOU (“LICENSEE” or “CUSTOMER”) AGREE TO THE TERMS OF THIS MASTER LICENSE AGREEMENT. IF YOU ARE ACCEPTING THESE TERMS ON BEHALF OF A COMPANY OR OTHER LEGAL ENTITY, YOU REPRESENT AND WARRANT THAT YOU HAVE FULL AUTHORITY TO BIND SUCH COMPANY OR OTHER LEGAL ENTITY TO THESE TERMSIN WHIAFS CASE THE TERMS “LICENSEE” WILL REFER TO SUCH ENTITY. THE AGREEMENT IS EFFECTIVE AS OF THE DATE YOU ACCEPT THESE TERMS (“Effective Date”). IF YOU DO NOT HAVE SUCH AUTHORITY, OR IF YOU DO NOT AGREE TO THESE TERMS, DO NOT DOWNLOAD, INSTALL, COPY, ACCESS, CLICK ON AN “ACCEPT” BUTTON, OR USE THE PROGRAM; AND PROMPTLY RETURN THE UNUSED MEDIA, DOCUMENTATION, AND PROOF OF ENTITLEMENT TO THE PARTY FROM WHOM IT WAS OBTAINED. IF THE PROGRAM WAS DOWNLOADED, DESTROY ALL COPIES OF THE PROGRAM. This Master License Agreement (“ Agreement ”)is made on [*************] by and between Licensee and HCL Technologies Limited , a company duly organized and existing under the laws of India and having its registered offices at 806 Siddharth, 96 Nehru Place, New Delhi -110019 (“Licensor ” or “HCL ”) and [*************] (“Licensee ”), and governs the receipt and use of IAFS and related Support (as defined below). Licensor and Licensee hereinafter referred to individually or collectively, as “Party ” or “Parties .” 1. Definitions. In addition to the terms defined above and elsewhere in this Agreement, the following terms will have the meaning set forth below: 1.1. “Affiliate ” means an entity that controls, is controlled by, or shares common control with HCL or Licensee, where such control arises from either (a) a direct or indirect ownership interest of more than
50%, or (b) the power to direct or cause the direction of the management and policies, whether through the ownership of voting stock, by contract, or otherwise, equal to that provided by a direct or indirect ownership of more than 50%. 1.2. “Documentation ” means guides, manuals, and other technical information in printed and machine - readable form for developing features that support IAFS . 1.3. “Feedback ” means (i ) Licensee's requirements, input, comments, responses, opinions, feedback and errata, concerning the definition, design or validation of IAFS and Documentation or (ii) Licensee's technical system requirements for HCL to include in the Licensed Software spec ifications, design or validation. 1.4. “Fees ” means license, Support, and other fees as specified in an Order or provided under this Agreement. 1.5. “Intellectual Property Rights ” or “ IPR” means any ideas, whether or not patentable, inventions, discoveries, processe s, works of authorship, marks, names, know -how, and any and all rights in such materials on a worldwide basis, including any rights in patents, inventor’s certificates, utility models, copyrights, moral rights, trade secrets, mask works, and all related, similar or other intellectual property rights recognized in any jurisdiction worldwide, including all applications and registrations with respect thereto. 1.6. “Licensed Capacity ” means the quantity of each IAFS node licensed as specified in an Order. 1.7. "Object Code " means software (IAFS ), including all computer programming code, entirely in binary form, wh IAFS is directly executable by a computer and includes those help, message, overlay, and other files necessary for supporting the intended use of the executable code.
1.8. “Open Source Software” means an open source or other license that requires, as a condition of use, modification, or distribution, that any resulting software must be (i) disclosed or distributed in Source Code form; (ii) licens ed for the purpose of making derivative works; or (iii) redistributable at no charge. 1.9. “Order ” means an agreed written or electronic document, subject to the terms and conditions of this Agreement that identifies IAFS to be licensed, the Licensed Capacity thereof, applicable Fees, and the Support to be purchased. 1.10. “Prerequisite Materials ” means any prerequisite software or materials (third party and/or HCL licensed) required by the Licensee, wh IAFS are not part of IAFS and are identified in the system requirements for IAFS . 1.11. “Problem ” means a reproducible condition that causes the operation of IAFS to deviate from its Documentation, so as to impact Licensee’s ability to use IAFS in the manner described in the Documentation. 1.12. “Program(s) ” means the Object Code of IAFS (including Third Party Software) and all accompanying Documentation delivered to Licensee, including all items delivered by HCL to Licensee under Support, but excluding Open Source Software. 1.13. “Source Code ” means computer programming code in human readable form and related system level documentation, including all associated comments, symbols, and any procedural code such as job control language. 1.14. “Supplemental Terms ” means document that provides information and any additional terms specific for IAFS and is attached as an Exhibit XX. 1.15. “Support” means the basic support services provided by HCL that available for IAFS as further specified in an Order or provided under this Agreement. 1.16. “Territory ” means the country or countries where Licensee is licensed to install IAFS as further detailed in an Order.
detailed in an Order. 1.17. “Third Party Software ” means third party software, libraries, and components incorporated in or included with IAFS , but excluding Open Source Software. 2. Agreement Structure. Licenses are granted and Support is obtained solely in connection with Orders executed by both parties. Each Order is subject to the terms of this Agreement and deemed to be a discrete contract, separate from each other Order, unless expressly stated otherwise therein. Orders may be entered into under this Agreement by and between (a) HCL or an Affiliate of HCL; and (b) the Licensee or an Affiliate of Licensee. With respect to an Order, the term HCL (or Licensor) or Licensee (or Licensee) will be deemed to refer to the entities that execute such Order. Neither execution of this Agreement nor anything contained herein will obligate either Party to enter into any Orders. In the event an Order is proposed by HCL, and is deemed to constitute an offer, then acceptance of such offer is limited to its terms. In the event Licensee proposes or accepts an Order by submitting a purchase order, order document, acknowledgment, or other communication, then regardless of whether HCL acknowledges, accepts, fully or partially performs under any such document, HCL objects and rejects any additional or different terms in such document and none of such additional or different terms will become part of the agreement between the Parties even if HCL uses or refers to such document for invoicing purposes. 3. License Grant 3.1. Subject to the terms, conditions, and other restrictions set forth in this Agreement and a valid, executed Order (including timely payments of any Fees therein), HCL grants to Licensee a non -exclusive, non- transferable, limited, and revocable license, without the right to sublicense, under HCL IPR, to install, access, and use IAFS (i) up to the Licensed Capacity; (ii) for Licensee internal business purposes; and
(iii) in accordance with the Documentation and the applicable Order. For avoidance of doubt, Licensee has no rights to create derivative works, assign, distribute, lease, rent, or otherwise transfer IAFS . 3.2. Licensee Affiliates may install, access, and use IAFS and Support under the terms of this Agreement, and Licensee is fully responsible for its Affiliates compliance with the terms of this Agreement and the Order.
3.3. Licensee hereby acknowledges that IAFS may contain Open Source Software and may require Prerequisite Materials . In the event that Third Party Software is included in the Program(s), Licensee agrees that unless separate supplemental terms are communicated via the release notes, the terms contained in this Agreement shall apply to use of such Third Party Software . In the event that IAFS rely on Prerequisite Materials, Licensee agrees that HCL and its Affiliates have not obtained or conveyed to Licensee any Intellectual Property Rights to use the applicable Prerequisite Materials. 4. License Restrictions 4.1. Restrictions . Except for the limited licenses expressly granted in Section 0, Licensee has no further rights in IAFS , whether express, implied, arising from estoppel or otherwise. Further restrictions regarding Licensee’s use of any and all Program(s) are set forth below. Except as expressly authorized herein, Licensee will not: 4.1.1. prepare any derivative works, or otherwise use, copy, modify, distribute, assign, sublicense, lease, rent, or otherwise transfer IAFS , except to the extent required by law; 4.1.2. use IAFS in an outsourcing or service bureau environment on its behalf and/or on behalf of non - affiliated third parties or allow IAFS to be used by an outsourcing or service bureau provider on behalf of the Licensee; 4.1.3. distribute IAFS to end -users as on -premises distributions or offer IAFS as a cloud service or software -as-a-service to any end-users; 4.1.4. reverse engineer, reverse assemble, reverse compile, translate, or otherwise attempt to discover the Source Code form of any Program(s) that are provided in Object Code form, except as permitted by the national or regional law of the places where the Licensee does business (without the opportunity for contractual waiver), and then only with r espect to the particular copy of Object
Code incorporated into that particular Program. 4.1.5. use any of IAFS ’s components, files, modules, audio -visual content, or related licensed materials separately from IAFS ; 4.1.6. attempt to disable or circumvent any of the licensing mechanisms within IAFS ; 4.1.7. alter or remove any copyright, trademark or patent notice(s) in IAFS ; and 4.1.8. use IAFS in a way that requires the Programs to be licensed as Open Source Software. 5. Feedback. Licensee is not obligated to provide Feedback to HCL. To the extent that Licensee provides Feedback to HCL, Licensee hereby grants to HCL a worldwide, non-exclusive, perpetual, irrevocable, royalty - free license, with the right to sublicense, under any and all Licensee IPR in and to the Feedback to make, use, sell, offer to sell, have made, import, reproduce, prepare derivative works, distribute, incorporate or otherwise utilize such Feedback. 6. Ownership. Licensee acknowledges that, as between Licensee and HCL, HCL has exclusive right, title and interest in and to all of the IPR in and to IAFS . Notwithstanding the use of the terms “purchase,” “sale”, or any similar terminology in connection with a transactio n contemplated by this Agreement, IAFS is licensed, not sold. 7. Delivery. During the term of this Agreement, and subject to Licensee making timely payments of any Fees in accordance with Section 11, HCL will make Program(s) avail able to Licensee. For Programs that are delivered electronically, Licensee agrees upon request from HCL to provide HCL with documentation supporting that the designated items were received electronically. For Programs that HCL provides to Licensee in tangible form, HCL fulfils its shipping and delivery obligations upon the delivery of such items to the HCL -designated carrier, unless otherwise agreed in writing by Licensee and HCL. The Programs are
accepted the day HCL delivers them either p hysically to the carrier or by providing access code(s) for electronic download, whIAFS ever occurs first. 8. Updates 8.1. If IAFS is replaced by a trade -up Program, the license for IAFS getting replaced will be promptly terminated. 8.2. When Licensee receives an update, fix, or patch to a Program, Licensee accepts any additional or different terms that are applicable to such update, fix, or patch that are specified in its Documentation.
If no additional or different terms are provided, then the update, fix, or patch is subject to the terms and conditions of this Agreement. 8.3. If IAFS is replaced by update, Licensee agrees to promptly discontinue use of the replaced Program. 8.4. Based on industry directions and technology changes, Licensor may discontinue further releases of IAFS . In such a situation, Licensor may continue to ship released versions of Programs, and all shipped versions will be governed by this Agreement. 9. Support 9.1. Licensee is automatically enrolled in Support for IAFS identified in an Order for the duration of the respective Order at no additional cost. HCL may offer and Licensee may purchase additional support, such as premium support, via the execution of a separat e contract. A further description of Support is available at https://www.hcltech.com/products -and-platforms/suppo rt (“Support Website”) and incorporated herein by reference. 9.2. HCL will provision and provide Support in accordance with the terms on the Support Website. Support is provided according to the support plan defined on the Support Website. HCL will only support a Program if it is used with third -party equipment, operating sy stem, hardware, and third -party software, including database server systems, networks, application server systems, and Licensee systems (collectively, “Platforms”) whIAFS meet the standards set forth in the applicable Documentation. Licensee will allow HCL reasonable access (including remote access) to IAFS and the supporting Platf orms, equipment, systems, documentation, and services, as necessary to perform Support services. Support does not include training on IAFS , Prerequisite Software or P latforms nor does it include any on-site diagnosis or on-site problem resolution. 9.3. HCL Program Support provides maintenance and technical support to Licensee for IAFS specified in
an Order. Support is limited to the specific release(s) of IAFS determined by H CL. Support for a particular version or release of a Program is available only for 3 years period OR until HCL withdraws Support for that Program's version or release (an “End of Support Release”). When Support is withdrawn, Licensee must upgrade to a supported version or release of IAFS to continue to receive Support. However, HCL will continue to offer, for an additional Fee to be mutually agreed -upon, the following extended support for End of Support Releases for so long as Licensee subscribes to Support for IAFS by: (i) answering Licensee’s routine, short duration installation and usage (how -to) questions; and (ii) answering Licensee’s code -related questions. However, in such cases, HCL will only provide existing code patches and fixes and will not develop or provide new patches or fixes for End of Support Releases. 9.4. HCL will use commercially reasonable efforts to provide resolution to each Problem submitted by Licensee in accordance with the Support Website. All Problems reported by a Support contact will be logged by a technology support engineer and assigned a tracking number. Licensee will be notified of the tracking number and should use this number in all f uture communication with HCL relating to such Problem. The severity level of a Problem will be determined in accordance with the applicable criteria set forth on the Support Website. HCL will use commercially reasonable efforts to resolve Problems within t he applicable designated timeframes set forth on the Support Website. In the event a Problem is not resolved within the designated timeframes, then HCL will escalate resolution in accordance with the procedures on the Support Website. Licensee will make re asonable efforts to assist HCL in identifying, isolating, and duplicating a Problem and will not hinder HCL’s ability to achieve Problem resolutions.
9.5. While HCL Support is in effect, HCL may make available defect corrections, restrictions, bypasses, new versions, releases, or updates available as part of Support (“Updates”). HCL will determine in its discretion the content and timing of all Updates. Updates will not be issued on any regular basis. If the solution to a Problem has already bee n made in a release later than the release Licensee is then using, then the solution to the Problem will require Licensee to migrate to the release in IAFS the Problem has been resolved. Updates will be considered part of IAFS , as applicable, and will be governed by and used under the terms and conditions set forth in this Agreement. Except as otherwise set forth in an Order, Statement of Work, or other agreement by the Part ies, Licensee will be responsible for installing and implementing each Update. HCL will provide Licensee with documentation regarding any specific
installation requirements for the Update. Once Support has been allowed to lapse, HCL will cease providing Updates (even Updates that were previously made available during Support IAFS Licensee chose not to accept). 9.6. Support does not cover problems, failures, or defects in the Programs caused by: (a) the misuse of or damage to the Program; (b) modificat ions to IAFS not made by or as authorized in writing in advance by HCL; (c) combination or use of IAFS with other software or hardware not provided or approved in writing by HCL; or (d) use of the Program in an operating environment other than that described in the Documentation or system requirements. HCL reserves the right to charge at HCL’s then -current standard hourly rates for any work performed by HCL that was found to be caused by the foregoing exclusions. To the extent a problem arises out of any Prerequisite Sof tware, Platform, hardware or services, Licensee will have the responsibility to contact the appropriate third party and obtain a resolution for the problem. 9.7. HCL may change its Support terms to be effective upon Licensee’s support anniversary date. HCL reserves the rights to discontinue Support for IAFS (including for prior releases or outdated versions of a Program) if HCL generally discontinues such services f or all licensees of such Program, provided such discontinuance of Support will be applicable from the next Support renewal term. If Licensee terminates Support, but then re-enrolls in Support, HCL reserves the right to charge a reinstatement Fee. 10. Licensee Data and Databases 10.1. To assist Licensee in isolating the cause of a problem with IAFS , HCL may request that Licensee (i) allow HCL to remotely or physically access Licensee’s system, or (ii) send Licensee information or system data to HCL. However, H CL is not obligated to provide such assistance unless HCL and
Licensee enter a separate written agreement or Order under IAFS HCL agrees to provide to Licensee that type of Support, IAFS is beyond HCL’s warranty obligations in this Agreement. Licensee acknowledges that HCL uses information about errors and problems to improve its products and services and to assist with its provision of related Support offerings. Licensee grants HCL the right to use such information and other feedback regarding IAFS for these purposes, including the right to use HCL entities and subcontractors (including in one or more countries other than the one in IAFS Licensee is located). 10.2. Licensee remains responsible for (i) any data and the content of any database Licensee makes available to HCL (“Licensee Data”); (ii) the selection and implementation of procedures and controls regarding access, security, encryption, use, and transmission of data (including any personally -identifiable data); and (iii) backup and recovery of any database and any stored data, including all Licensee Data. Licensee will not send or provide HCL access to any personally identifiable information, w hether as part of Licensee Data or in electronic or any other form, and will be responsible for reasonable costs and other amounts that HCL may incur relating to any such information intentionally or mistakenly provided to HCL or to the loss or disclosure of such information by HCL, including liabilities arising out of any third party claims. 11. Payments . 11.1. Fees . Licensee will pay any and all Fees as detailed in an Order. All amounts in this Agreement are in United States Dollars (USD). Licensee will pay HCL for the amounts due, owing, and duly invoiced under this Agreement within thirty (3 0) days of the date of invoice. Licensee shall make all payments pursuant to this Agreement through electronic transfer of funds to the designated bank accounts as
nominated by the HCL in writing. Overdue amounts payable under an Order will bear interest from the original due date at the rate of one percent (1%) per month or the maximum legal rate, IAFS ever is less. 11.2. Taxes . Licensee agrees to bear any withholding tax liability as may be required by law and would increase payment due under the Agreement by such an amount so that the net payment made to HCL after deduction of applicable withholding tax is the same, had there been no withholding tax applicable. 11.3. Licen se Compliance . Licensee agrees that HCL may, no more than one time per twelve (12) month period, audit the software logs of Licensee, its Affiliates, consultants, service providers and contractors (collectively, “Licensee Entity(ies) ”), relating to the Program in order to verify their use in compliance
with this Agreement and/or the Order. HCL may make copies of any such software logs to the extent necessary to verify Licensee’s compliance with the terms hereof. HCL may conduct the audit itself or at its option engage an independent third party to do such audit, provided that such third party is subject to confidentiality obligations consistent with this Agreement. The audit may be conducted at any sites of Licensee Entities, where the Program is installed, used or accessed from, including remotely. HCL will bear its own costs in connection with an audit. HCL will provide fifteen (15) calendar days’ notice prior to an audit. Any such audit will be performed during Licensee Entity’s normal business hours and in a manner that minimizes the disruption to its business. Licensee Entities will provide all assistance reasonably necessary for HCL to carry out such audit. If the audit reveals underpayments, Licensee will promptly make such payments. If the audit reveals under -reporting of usage, Licensee will promptly pay for the differentials at HCL’s then list price fo r the Program. HCL’s rights and remedies in this Section will be without prejudice to other rights and remedies HCL has under this Agreement or in any Order, at law or in equity. HCL’s rights under this provision will survive any termination or expiry of an Order or this Agreement for two years. 12. Term and Termination . 12.1. Term . Unless earlier terminated pursuant to the terms of the Agreement, the initial term of this Agreement is three (3) years from the Effective Date (the “Initial Term”). Unless either Party gives the other Party written notice thirty (30) days prior to the expiration of the then current term, this Agreement will automatically renew for successive periods of one (1) year each. 12.2. Termination by HCL. HCL may terminate this Agreement and any Order upon written notice to Licensee if:
Licensee if: 12.2.1. Licensee fails to pay the applicable Fees due under the Order within thirty (30) days of receipt of written notice from HCL for non-payment; 12.2.2. Licensee violates the IPR of HCL, its Affiliates, or its licensors or uses IAFS outside the scope of the license; 12.2.3. Licensee commits any material breach of this Agreement and fails to cure such breach within thirty (30) days after HCL notifies Licensee in writing of the breach; or 12.2.4. Licensee (i) files or has filed against it a petition in bankruptcy, (ii) has a receiver appointed to handle its assets or affairs, or (iii) makes or attempts to make an assignment for benefit of creditors. 12.2.5. HCL’s rights to terminate are in addition to any other rights HCL may have. 12.3. Effect of Termination or Expiration . In the event of termination or expiration of this Agreement, in whole or in part: 12.3.1. All licenses granted hereunder will terminate; 12.3.2. Licensee will return to HCL and/or certify that it has destroye d all copies of IAFS and Documentation, IAFS is in the possession of the Licensee; and 12.3.3. all Support obligations under the Agreement or an Order will terminate. 13. Confidentiality . Except as otherwise expressly permitted in this Agreement, Licensee will hold in confidence IAFS , Documentation and all other non-public or proprietary information made available by Licensor (“Confidential Information ”). Licensee agrees that the Programs and Documentation furnished by HCL will be treated as proprietary trade secrets of Licensor, and Licensee will not make any Confidential Information available in any form to any person other than to its employees and to contractors located on its premises with a need to know, subject to restrictions no less stringent than those contained herein (in the case
of nonemployees such restrictions will be contained in a written agreement executed by the applicable contractor). Licensee represents to Licensor that it maintains a system of confide ntiality to protect its own confidential business information, including written agreements with employees, and that the Confidential Information will be protected by such system using no less than a reasonable degree of care. If Licensee at any time becom es aware of any unauthorized use or disclosure of Confidential Information, Licensee will promptly and fully notify the Licensor of all facts known to it concerning such unauthorized use or disclosure
and reasonably cooperate with Licensor in seeking a protective order or other appropriate remedy to limit such disclosure. 14. Warranties and Exclusions 14.1. HCL warrants that (i) IAFS will perform substantially in accordance with its Documentation f or the duration of the relevant order (the “ Warranty Period ”); (ii) HCL has used commercially reasonable efforts consistent with industry standards to scan for and remove any software viruses; and (iii) other than passwords or license keys that may be required for the operation of IAFS , there are no codes that are not addressed in the Documentation and that are designed to delete, interfere with, or disable the normal operation of IAFS in accordance with the License (the “Warranty ”). 14.2. THE LIMITED WARRANTIES EXPRESSLY SET FORTH IN SECTION 14.1 ARE LICENS EE’S EXCLUSIVE WARRANTIES. HCL DISCLAIMS ALL OTHER WARRANTIES OR CONDITIONS, EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, ANY IMPLIED WARRANTIES OR CONDITIONS OF MERCHANTABILITY, SATISFACTORY QUALITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND ANY WARRANTY OR CONDITION OF NON - INFRINGEMENT. SOME STATES OR JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF EXPRESS OR IMPLIED WARRANTIES, SO THE ABOVE EXCLUSION MAY NOT APPLY TO LICENSEE. IN THAT EVENT, SUCH WARRANTIES ARE LIMITED IN DURATION TO THE WARRAN TY PERIOD. NO WARRANTIES APPLY AFTER THE WARRANTY PERIOD. SOME STATES OR JURISDICTIONS DO NOT ALLOW LIMITATIONS ON HOW LONG AN IMPLIED WARRANTY LASTS, SO THE ABOVE LIMITATION MAY NOT APPLY TO LICENSEE. 14.3. THE WARRANTIES IN THIS SECTION 14 ARE PROVIDED SOLELY BY THE HCL ENTITY LICENSING IAFS AND NOT BY A THIRD PARTY OR ANY OTHER HCL ENTITY. THE DISCLAIMERS IN THIS SECTION 14, HOWEVER, ALSO APPLY TO ALL HCL ENTITIES AND THEIR LICENSORS AND SUPPLIERS OF THIRD PARTY SOFTWARE. . THOSE SUPPLIERS PROVIDE SUCH SOFTWARE WITHOUT WARRANTIES OR CONDITION OF ANY KIND.
14.4. The exclusive remedy for any breach of the foregoing Warranty will be that HCL, at its own expense, and in response to a written notice of a warranty claim, will at its option (i) repair or replace IAFS to conform to the above standard, or (ii) refund to Licensee amounts paid for the non -conforming Program(s). 15. Indemnification 15.1. HCL will settle and, at its election, defend, any claim brought in any suit or proceeding against Licensee based upon an allegation that any Program(s) furnished hereunder constitutes a direct infringement of any patent, trade secret or copyright, and HCL will pay all damages and costs finally awarded against Licensee for the claim. In the event of any claim, allegation, or suit, HCL, in its sole discretion, may reengineer IAFS in a manner that removes the infringing material, replace IAFS with non-infringing software, or terminate the Agreement. HCL will not be liable for any costs or damages and will not indemnify or defend Licensee to the extent such action is based upon a claim arising from: 15.1.1. modification of IAFS by a party other than HCL after delivery by HCL; 15.1.2. use of IAFS in combination with hardware or software not provided by HCL, unless (i) the Documentation refers to a combination with such hardware or software (without directing Licensee not to perform such a combination); or (ii) such combination achieves functionality described in the Documentation (and the Documentation does not direct Licensee not to perform such combination); 15.1.3. any unauthorized use of IAFS ; or 15.1.4. Licensee’s failure to incorporate updates or upgrades that would have avoid ed the alleged infringement.
15.2. The foregoing obligations are conditioned on the following: (i) HCL is notified promptly in writing of such claim; (ii) HCL controls the defense or settlement of the claim; and (iii) Licensee cooperates reasonably and gives all necessary authority, information and assistance. 16. Limitation of Liability 16.1. IN NO EVENT WILL EITHER PARTY (OR HCL’S SUPPLIERS) BE LIABLE FOR ANY SPECIAL, INCIDENTAL, INDIRECT, OR CONSEQUENTIAL DAMAGES WHATSOEVER (INCLUDING, BUT NOT LIMITED TO, DAMAGES FOR LOSS OF PROFITS OR CONFIDENTIAL OR OTHER INFORMATION, FOR BUSINESS INTERRUPTION, FOR PERSONAL INJURY, FOR LOSS OF PRIVACY ARISING OUT OF OR IN ANY WAY RELATED TO THE USE OF OR INABILITY TO USE IAFS , OR OTHERWISE IN CONNECTION WITH ANY PROVISION OF THIS AGREEMENT, EVEN IF THE PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES AND EVEN IF THE REMEDY FAILS OF ITS ESSENTIAL PURPOSE. 16.2. EXCEPT FOR BREACHES OF LICENSE GRANTS IN SECTION 3, RESTRICTIONS IN SECTION 4, CONFIDENTIALITY IN SECTION 13, AND LICENSEE’S PAYMENT OBLIGATIONS, IN NO EVENT WILL EITHER PARTY'S (OR HCL’S SUPPLIERS) TOTAL CUMULATIVE LIABILITY TO THE OTHER PARTY FOR ANY DIRECT DAMAGES ARISIN G FROM THIS AGREEMENT, EXCEED THE SUM PAID OR PAYABLE TO HCL BY LICENSEE UNDER THIS AGREEMENT FOR THE PRECEDING TWELVE (12) MONTHS FROM THE DATE THE CLAIM AROSE. 16.3. The foregoing disclaimers, limitations, and exclusions may be invalid in some jurisdictions an d apply only to the extent permitted by applicable law or regulation in Licensee’s jurisdiction. Licensee may have additional rights that may not be waived or disclaimed. HCL does not seek to limit Licensee's warranty or remedies to any extent not permitted by law. 17. Other Terms 17.1. Conflict . In the event of a conflict between this Agreement and an Order attached to this Agreement, the terms of the Order will prevail solely with respect to such Order and only to the extent that such
conflicting terms are necessary to satisfy the requirements of applicable, local laws; otherwise the terms of this Agreement will prevail. 17.2. Force Majeure . Neither Party will be liable for any failure to perform due to unforeseen circumstances or causes beyond its reasonable control, including, but not limited to, acts of God, war, riot, embargoes, acts of civil or military authorities, delay in delivery by vendors, fire, flood, accident, strikes, inability to secure transportation, facilities, fuel, energy, labor, or materials. In the event of force majeure, time for delivery or other performance will be extended for a period equal to the duration of the delay caused thereby. 17.3. Export . Licensee will comply with all applicable export and import laws and associated embargo and economic sanction regulations, including those of the United States, that prohibit or restrict the export, re-export, or transfer of products, technology, services, or data, directly or indirectly, to certain countries, or for certai n end uses or end users. Licensee acknowledges that IAFS is subject to U.S. export laws and regulations. Licensee agrees that, unless authorized by the U.S. export license or regulation, it will not export or re -export IAFS provided by HCL under this Agreeme nt or an Order to (i) those countries (or nationals of countries) considered embargoed/terrorist countries under U.S. export laws and regulations or (ii) prohibited end users or end uses, including but not limited to: nuclear, space or missiles, and weapons systems (including chemical and biological). At the time of this Agreement, those countries considered embargoed/terrorist are: Cuba, Iran, North Korea, Sudan and Syria. 17.4. Anti -Corruption Laws. Each Party will comply, at its own expense, with all applicable laws, including, without limitation, all laws prohibiting corruption and bribery (such as, if applicable, the U.S.
Foreign Corrupt Practices Act of 1977), laws governing transactions with government and public entiti es, antitrust and competition laws, insider trading, securities, and financial reporting laws, laws governing consumer transactions, and laws regarding data privacy, where such compliance has any direct or indirect connection or relation to this Agreement or either Party’s exercise of rights or satisfaction of obligations under this Agreement.
17.5. Notices. All notices required or permitted by this Agreement will be in writing and will be valid and sufficient if sent by (i) registered or certified mail, return receipt requested, postage prepai d; (ii) by facsimile (provided the receipt of the facsimile is evi denced by a printed record of completion of transmission); or (iii) by express by express mail or courier service providing a receipt of delivery. Notices will be effective upon receipt as demonstrated by reliable confirmation. Notices will be addressed to the Parties using the contact information given in an the applicable Order or this Agreement. Either Party may change its address or other contact information by a notice given to the other Party in the manner set forth above. 17.6. Limitation of Claims. Unless otherwise required by applicable law without the possibility of contractual waiver or limitation: (i) neither party will bring a legal action, regardless of form, for any claim arising out of or related to this Agreement more than two (2) years after the cause of action arose; and (ii) upon the expiration of such time limit, any such claim and all respective rights related to the claim lapse. 17.7. Survival . All of the provisions in Sections 1, 4, 5, 6, 11, 12, 13, 16, and 17 w ill survive expiration or termination of this Agreement. 17.8. Assignment. HCL may assign or delegate its rights and/or obligations, or any part thereof under this Agreement to any or all of its subsidiaries. Licensee will not assign or transfer this Agreement or an Order executed under this Agreement, without the written consent of the Licensor. Except as mentioned herein, any attempted assignment or transfer by Licensee of this Agreement or Programs is null and void. 17.9. Relationship of Parties. The relationship between the Parties is that of independent contractors. This Agreement does not constitute a partnership or joint venture between Licensee and HCL. Licensee is
not the representative or agent of HCL and HCL is not the representative or agent of Licensee and neither will so hold itself out publicly or to any third party or incur any liability for the other Party. 17.10. Modifications . This Agreement may be modified or amended only by a written instrument duly signed by authorized representatives of Licensee and HCL. 17.11. Severability . All rights and remedies whether conferred hereunder, or by any other instrument or law will be cumulative and may be exercised singularly or concurrently. The failure of any Party to enforce any of the provisions hereof will not be construed to be a waiver of the right of such Party thereafter to enforce such provisions. The terms and conditions stated herein are declared to be severable. If any provision or provisions of this Agreement will be held to be invalid, illegal or unenforceable, the validity, legalit y and enforceability of the remaining provisions will not in any way be affected or impaired thereby. 17.12. Counterparts . This Agreement may be executed in several counterparts, each of wh IAFS will be deemed an original, but all of whIAFS together will constitute one and the same instrument. 17.13. Injunctive Relief . Licensee agrees that preliminary injunctive or other equitable relief will be a necessary and proper remedy in the event of a breach of this Agreement in violation of HCL’s IPR, in addition to all other rights that HCL has at law or in equity. 17.14. Governing Law and Jurisdiction . Any claims arising under or relating to this Agreement will be governed by the internal substantive laws of the State of California or federal courts located in California, without reference to (i) any conflicts of law principle that would apply the substantive laws of another jurisdiction to the Parties’ rights or duties; (ii) the 1980 United Nations Convention on Contracts for the International Sale of Goods; or (iii) other international laws. Each Party hereby
irrevocably agrees to submit to the jurisdiction and venue in the courts of the State of California f or all disputes and litigation arising under or relating to this Agreement. 17.15. Public Announcement . Neithe r Party will publicly announce or create a press release referencing this Agreement, its contents or its related activities without the prior written consent of the other Party. 17.16. Entire Agreement . This Agreement is the entire agreement between HCL and Licen see relating to the Program(s) and it supersedes all prior or contemporaneous oral or written communications,
Agreed: proposals and representations with respect to IAFS or any other subject matter covered by this Agreement. LICENSEE: _______________________ HCL. By: Typed Name: Title: Date: By: Typed Name: Title Date:
IAFS -Field Support Comparison and Recommendation deck
Copyright © 202 3HCL Technologies Ltd. | Confidential 2 Use Cases Productivity Customer Satisfaction Response time Collect relevant Historical data Mine critical information By Using AI/MLOptimize task, Improve process and productivity Field support solution incorporates cutting -edge AI/ML and Generative AI technologies to optimize field support operations . It built on top of iTS framework and streamlines ticket resolution, reduce manual efforts, improve product support quality to boost efficiency and productivity for field support teams . Only with Generative AIUse cases with GenAI and ML both
Company Accelerator Capabilities Features Top Clients Industry Covered Pricing Microsoft Microsoft Dynamics 365 Field Service1.Self-service Scheduling 2.Faster issue resolution 3.Streamline work order management 1. Self -service appointment Scheduling 2. Automate customer communication 3. Provide post engagement surveys 4. Provide tools directly in the flow of work 5. Streamline tasks using the mobile experience 6. Resolve issues quickly with remote collaboration 7. Streamline work order by using Generative AI 8. Intelligent Recap feature to stay up to date 9. Track performance with real time reporting 1. G&J Pepsi 2. Phillips 3. Santam 4. UD Trucks 1. Manufacturing 2. IT Service 3. Healthcare and Biotech Industry 4. Retail Industry 5. Finance (non -banking) Industry $20-$300 per user/ per month PraxedoPraxedo Field Service Management1. Scheduling 2. dispatching 3. Tracking 4. Reporting 5. Invoicing1. Configurable web app that allows define organization, business processes, and workflows. 2. Advanced scheduling based on skillset, travel time, and customer availability. 3. Dynamic scheduling dashboard 4.Mobile app for online and offline work 5. Inventory tracking 6. Customer portal that update real time communication.
communication. 7. APIs that enables to integrate Praxedo with client existing ERP, CRM, or accounting software. 1. Constructel 2.Altitute Infra 3. Premier Lifts 4. Simoneau 5. Veolia 6. Engie 7. Suez1. Manufacturing 2. Energy and Utilities 3. Construction Industry 4. Insurance (except health) Industry 5. Hardware Industry 6. Banking Industry 7. Energy and Utilities Industry 8. Telecommunication Industry $33 -$79 per user/ per month SalesForceSalesforce Field Service1. Scheduling 2. dispatching 3. Tracking 4. Reporting 5. Invoicing1.Scheduling and Optimization 2. Mobile productivity Tools 3. Dispatch Management 4. Asset service Management 5. Visual Remote Assistance 6.Appointment Assistance 1. Uber Eats 2. Western Union 3. Humana 4. The Auto club group 5. Schneider Electric 6. Pella windows and doors1. Manufacturing 2. Energy and Utilities Industry 3. Consumer Goods Industry 4. Telecommunication Industry. 5. Healthcare and Biotech 6. Media Industry 7. Construction Industry $25-$500 per user/ per month OracleOracle field Service 1. Scheduling 2. dispatching 3. Tracking
3. Tracking 4. Reporting 5. Invoicing1. Forecasting and workload management 2. Capacity Management 3. Scheduling and routing 4. Technician Enablement 5. Customer Self -Service 6. IOT and connected equipment 7. Service Logistics 1. Badger Daylighting 2. Enersense 3. Vivint smart Home 4.Ricoh 5. Cablevision 6. BOSCH 1. Energy, Utilities & resources 2. Manufacturing Industry 3. Service Industry 4. Telecommunication $100 -$225 Per user/Per Month
Software Starting price Key features Zendesk$19 per agent/monthOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging System integrations Ticket assignment flexibility No-code chatbot builder Zoho Desk$20 per user/monthOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging System integrations Ticket assignment flexibility No-code chatbot builder FreshdeskFree plan availableOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging System integrations Ticket assignment flexibility No-code chatbot builder LiveAgentFree plan availableOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging System integrations Ticket assignment flexibilitySoftware Starting price Key features HubSpot Ticketing SystemFree plan availableOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics, Tagging Ticket assignment flexibility, System integration SupportBee$15 per user/monthOmnichannel and intelligent routing Reporting and analytics Tagging, System integration, Ticket assignment flexibility TeamSupport$49 per agent/monthAutomations and workflows Agent interface with unified customer view Reporting and analytics Tagging, System integration, Ticket assignment flexibility HappyFox$39 per agent/monthOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging, System integration, Ticket assignment flexibility No-code chatbot builder Jira Service ManagementFree plan availableOmnichannel and intelligent routing Automations and workflows Agent interface with unified customer view Reporting and analytics Tagging, System integration, Ticket assignment flexibility
Web Help Desk by SolarWinds$19 per technician/monthAutomations and workflows Agent interface with unified customer view Reporting and analytics Tagging System integrations
deepsense.ai 2.Understand service MS Dynamics 365 Field Service SF Field Service Senti Sum Automation Anywhere
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