Seeq Launches AI Platform for Industrial Decision Support
New agentic AI capabilities integrate institutional knowledge and real-time data to streamline complex industrial workflows.
- By Jesse Jacobs
- Mar 03, 2026
Industrial analytics firm Seeq has released a new platform, Seeq Intelligence, aimed at centralizing expert knowledge and automating decision-making processes within manufacturing and industrial environments.
The platform addresses a growing reliance on siloed systems and the risk of talent loss by using artificial intelligence to capture and scale institutional expertise. By analyzing real-time operational data alongside historical decision patterns and domain knowledge, the system is designed to provide consistent insights across an enterprise.
A core component of the release is Agent Q, a domain-aware AI analyst. The tool uses natural language processing to synthesize unstructured data—including past analyses, historical events, and technical manuals—to provide investigators with traceable intelligence and recommended actions.
The update also includes a customizable agent builder, allowing users to automate multi-step workflows. These agents can be programmed to handle data retrieval, complex analytics, and reporting based on specific operational triggers or schedules.
To improve connectivity between different software environments, the platform features agent extensibility. This allows Seeq’s AI to securely connect with external customer systems, enabling users to retrieve work orders or trigger automated actions without switching between multiple interfaces.
"Seeq Intelligence represents a step change in how industrial companies create value," said Mark Derbecker, chief product officer at Seeq. "By synthesizing context, history, and domain expertise with advanced AI, we are providing a continuously learning system that sharpens decision-making."
The platform further incorporates document access capabilities, which extract information from semi-structured sources like equipment manuals and procedures to support automated summaries and technical inquiries.
Matthew Littlefield, president and research lead at LNS Research, noted that the technology provides an agentic layer capable of reaching across the operational technology stack to influence the speed and priority of strategic decisions.
The new features are available as part of the company's enterprise package.