Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 competitorsFailure 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. |
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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 |
1
Copyright © 2023 HCL Technologies | Confidential |
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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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