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TenForce Introduces AI Assistants Embedded in Daily EHS Workflows

Human-in-command AI helps EHS teams strengthen incident follow-up, permit risk assessment, without slowing work down

Quality Digest
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Tue, 03/24/2026 - 12:03
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(TenForce: Leuven, Belgium) -- TenForce, part of Elisa Industriq, has launched two AI assistants embedded directly into its EHSQ platform. One is an AI assistant for incident management, and the other an AI assistant for permit to work. Purpose-built for high-risk and regulated industries, these assistants support EHS and operations teams at the moments when decisions matter most—after incidents and before high-risk work begins.

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Both assistants operate seamlessly within existing workflows. They review information already entered by users, together with relevant historical and site-specific data, and suggest what may need attention. All AI-generated suggestions are visible, explained, and optional. Final decisions and accountability always remain fully with the user, ensuring AI supports professional judgment rather than replacing it.

AI Assistant for Incident Management: A better starting point for corrective and preventive actions

Incident follow-up quality often depends on the investigator’s experience, available time, and workload. The new AI Assistant for Incident Management helps teams build stronger corrective and preventive action plans by proposing relevant follow-up actions based on the incident context and past learnings from comparable cases.

By prompting likely actions early, the assistant reduces the risk of missed follow-up without adding administrative steps or slowing response.

Customer benefits

• More thorough and consistent follow-up, regardless of who handles the case
• Less time spent determining next steps
• Stronger prevention through better reuse of prior learnings

This supportive AI, embedded directly in existing workflows, keeps teams focused on execution instead of documentation.

AI Assistant for Permit to Work: A second set of eyes without a two-person workflow

The AI Assistant for Permit to Work provides a built-in “second set of eyes” during permit preparation. It identifies relevant hazards and controls based on similar jobs, tasks, and locations.

This helps teams prepare more complete permits and steadily strengthen the site’s risk registry without adding reviewers, approval steps, or process delays.

Customer benefits

• Lower operational risk through improved hazard identification
• Better reuse of risk knowledge across permits and sites
• Consistent permit quality at the same operational pace

The assistant supports permit owners and approvers, but it never replaces expertise, approves risks, or controls on its own.

Human-in-command by design

“AI should support professional judgment, not override it,” says Uroš Milošević, head of product and innovation at TenForce. “These assistants are designed to guide attention and prompt thinking while keeping responsibility exactly where it belongs, with the people managing incidents and permits every day.”

With both assistants:
• AI suggests, users decide
• No automatic approvals or hidden logic
• Full visibility and user control

Grounded in applied industrial AI expertise

TenForce’s AI approach builds on applied research, operational data expertise, and close collaboration with manufacturers in high-risk industries. As a contributor to the AI-PROFICIENT initiative, TenForce has helped shape responsible, human-centric AI practices for industrial environments.

Rather than introducing black-box automation, TenForce embeds AI where it adds practical value without compromising safety, accountability, or regulatory compliance. This approach is aligned with Elisa Industriq’s broader vision of pragmatic, explainable AI built for the realities of operational work.

Built for high-risk, regulated environments

The AI assistants are designed for teams working in complex, high-risk environments across manufacturing, food and beverage, and pharmaceuticals. They can be activated within existing TenForce workflows and scaled according to each organization’s AI maturity and governance model.

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