Seeq GenAI Assistant for industrial data

  • April 8, 2024
  • William Payne

Industrial data specialist Seeq has added a Generative AI resource to its industrial analytics platform. The Seeq AI Assistant supports users in managing analytics and using machine learning and AI resources on the platform.

Seeq provides on-demand access to industrial time series data, data contextualisation capabilities, and established intellectual property. The new AI Assistant builds on analytics, data science, machine learning and coding knowledge held in Seeq technical documentation and its knowledge base. Seeq also supports multiple providers and LLMs for organisational flexibility.

“With the Seeq AI Assistant, we expect to decrease our process experts’ learning curve for advanced analytics and machine learning by 50% or possibly more,” said Brian Scallan, Director of Continuous Improvement at Ascend Performance Materials. “For our extensive user base, this translates into immediate enhancements in process quality and yields, significantly elevating efficiency and value across the organisation.” “By combining GenAI with advanced industrial analytics, organisations can unlock new levels of efficiency, accuracy, and innovation that deliver measurable business impact,” said Dustin Johnson, Chief Technology Officer at Seeq. “Integrating the Seeq AI Assistant across the Seeq platform enables team members across industrial organisations to harness the power of GenAI to drive favourable operational excellence, profitability, workforce upskilling, and sustainability outcomes and stay ahead in an increasingly competitive landscape.”

“GenAI capabilities are a powerful inclusion in analytics software as a way to democratise AI and machine learning,” said Jonathan Lang, Research Director for IDC Industry Operations. “Based on conversations with industrial enterprises, GenAI offers a more natural interface to lower the barriers to data analytics, and Seeq has included features to alleviate one of the top concerns companies have about trust by including explainability to ensure the GenAI ‘shows its work’.”