## 4 The Approach with Canvass Analytics Platform  
Ref. [5] referred to the business model of Canvass Analytics (CA) [16]. Gradient Ventures is Google's AI-focused venture fund [17], which invests in and connects early-stage startups with resources in artificial intelligence. It was interesting to search in the portfolio of startups founded and find Canvass Analytics as one of them. This startup, which aroused interest for this research, developed a business model based on an AI-powered predictive analytics platform for industrial processes. Its customers include leading manufacturing and energy companies globally.  
Ref. [5] mentioned the startup CA as a leading provider of AI industrial software. Its patent-pending technology enables industrial companies to accelerate their digitization strategy by putting AI directly in the hands of plant operators--empowering them with data-driven insights to improve production processes and optimize assets.  
Unlike other solutions, CA empowers process engineers to quickly apply AI data applications without requiring coding skills. The solution offers prebuilt templates to minimize coding for process engineers, using a Low-Code/No-Code approach [18].  
Then, the value proposal of the CA business model focuses on shortening the adoption cycle of AI/ML in industrial environments by using prebuilt templates for manufacturing processes. The platform seven 7 templates: Forecasting, Anomaly Detection, Optimization, Simulation, Failure Prediction, and Defective Part Prediction. The template to use in each case depends on the nature of the process and the opportunity to address.  
These preconfigured applications allows users to have a model and evaluate results faster than people in the process. The adoption cycle begins working with the model offline, fed by data from the historian. In this way, the operators evaluate results and gain confidence by iterating through multiple experiments. Finally, the model is deployed into operations, this time ingested with real-time data.  
CA provides solution as a service (SaaS) ingesting in its platform, which is cloud-hosted; data in a data series format from MES; or Industrial Internet of Things (IIoT) solutions. The AI/ML platform is integrated with the shop floor solutions, and work with data in real time to provide the predictions to the process operators. A complex issue for the industrial environment, and a weakness reported by the study in [19]; namely, cybersecurity, is tackled by hosting the platform at Azure Microsoft Cloud. This cloud solution also gives the calculation power for the requirement of AI/ML models.  
Ref. [4] pointed out that the startup provides a solution that automates the entire data science process, eliminating consulting data science projects. The CA business model has accelerated the time to insights 12 times faster than other solutions and approaches. The solution was developed specifically for the industrial sector.  
CA's platform is being applied across the production process to improve quality, reduce energy consumption, and reduce waste in raw material processing, steelmaking and casting, and hot rolling. This has led to greater stability downstream in rolling processes, leading to more plant throughput, fast sales cycles, and less deterioration of its refractories. In addition, Canvass AI is being used to control cogeneration boilers to optimize fuel sources and consumption, optimize energy supply to plant demand, and reduce energy waste and fuel costs [20].