Cenevo, which specializes in lab management systems, automation, orchestration, data management and AI technology for life sciences, is introducing two new AI agents as part of its focus on helping scientists operate faster, smarter and with less manual overhead, without sacrificing control or compliance.
“Our AI initiatives are designed to eliminate manual work at the two biggest friction points in laboratory operations: getting knowledge into the system and turning that knowledge into action,” says Cenevo CEO Keith Hale. “We want to give scientists the power to use AI to autonomously solve complex, multi-step workflows, allowing them to focus on the more impactful aspects of their activities.”
The new agents are the AI Protocol Conversion agent and the AI Automation agent.
The AI Protocol Conversion agent automatically transforms legacy, “paper-based,” static documents and protocols into fully structured, reusable, and compliant protocols. The content is completely mapped and available within Labguru’s native elements, such as steps and forms. It preserves existing protocol structures and intent and eliminates manual copy-paste and reformatting.
The AI Automation agent allows scientists to describe what they want to automate, without needing programming expertise. The agent itself reduces implementation time and costs by 30-50%. It generates the underlying workflow logic and code automatically, with human-in-the-loop approvals and full audit trails.
The AI automation agent leverages Labguru data and integrations with external systems and gives scientists complete control over the process, from scientific intent to executable, event-driven workflows, which are fully visible and editable. They are triggered by experiment status, QC thresholds, or sample changes, keeping automation powerful, transparent, and fully compliant with FDA 21 CFR Part 11 and GxP requirements.
Combined, the AI Protocol Conversion and Automation agents create a continuous loop, from structured data to automated action. The Protocol Conversion Agent brings in knowledge, and the Automation Agent turns that structure into proactive workflows.
“With the addition of these new AI agents, and many more to come, scientists’ time will be freed to delve deeper into their research,” said Jonathan Gross, Cenevo Chief Product Officer. “Generating scientific results requires physical analyses by multiple instruments. That makes AI adoption more challenging than in data-only industries. That’s why we’re building on our existing foundation of integration and connectivity to help labs to accelerate their adoption of gen AI and agentic AI.”
