Canvass AI Revolutionizes Industrial AI with Hyper Data Analysis

Industrial AI software leader Canvass AI today announced the next evolution of its industrial AI software with Hyper Data Analysis™. Through an innovative use of generative AI, the Canvass AI software now incorporates learnings from text and visual-based data, adding it to production data streams, to advance traditional time-series-based AI insights.

Humera Malik, CEO, Canvass AI said, "We are harnessing the potential of GenAI to continuously innovate our approach to industrial problem-solving. Our strategy goes beyond merely adding a chatbot interface to our product. This cutting-edge capability is a deep dive into the realm of data analysis, yielding profound insights that drive superior outcomes. It's not just a step forward; it's a giant leap that expands the frontiers of what our customers can achieve in solving complex challenges, pushing the boundaries of what's possible in the industrial space."

Hyper Data Analysis makes sense of the plethora of unstructured text and visual data that often encompasses a manufacturing process and has many applications such as:

  • Identifying the quality or relevant properties of finished products by visually inspecting for anomalies;
  • Visual inspections can be incorporated using AI to determine the likely cause of defects;
  • Text-based maintenance logs can be turned into meaningful data that, coupled with process data, improves predictions of unplanned maintenance events in advance; and
  • Laboratory notes and "batch travellers" can be integrated with process and equipment data to provide more meaningful insights into product quality, providing simulated lab measurements or real-time quality predictions.

"Canvass AI enables holistic analysis of data that is both human and machine generated," added John Murdoch, VP Platform. "Canvass AI Solutions coupled with the Hyper Data Analysis capabilities in industrial use cases provide novel opportunities for manufacturers to optimize not only their assets and processes, but also their workflows. This combination of structured and unstructured data opens doors to new dimensions in AI-driven industrial solutions."


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