AI Agents in the Lab: How Scilligence Is Bringing Artificial Intelligence Into Everyday Research Workflows
A Platform Built for Every Drug Modality
Kicking off Scilligence’s three-part Fall Webinar Series, Steve Unger opened Part 1 with a simple premise: AI in the lab shouldn’t be a separate tool scientists have to context-switch into. It should be built into the platform they’re already using, available in real time, while they work.
The platform itself is built to handle every modality a research team might touch, small molecules, macromolecules, peptides, antigens, and drug conjugates, each registrable on its own or combined, with full traceability back to their components.
One Platform, Built in Modules
ELN, registration, inventory, and project management can each run standalone or connect into a single environment, no duplicate entry required. Unger drew on his own experience running this kind of system at a California biotech, including a detail worth flagging for any team working with a CRO: when your CRO runs on the same platform, migrating their data into your own system becomes dramatically simpler.
Experiments, Without the Manual Entry
The heart of the session was a live look at how the AI agent builds experiments for you, from an uploaded PDF, from an audio or video recording (so a scientist never has to pull off their gloves), or from a procedure simply dictated out loud. In every case, the agent confirms what it captured before anything gets finalized, keeping the scientist in control of the final record.
From there, the same agent can translate a completed procedure into another language without losing a single compound name, quantity, or unit, generate custom reports (including the kind of structured summaries patent teams need), and even route inventory requests through nothing more than a plain-language conversation.
Part 2 of the series (October) goes deeper on embedded third-party AI models for molecular design. Part 3 (November) covers lab automation and robotics.
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