TetraScience Technical Showcase Series

The models are capable. That's not the question anymore.

The question is whether you can deploy them in a regulated research environment with full auditability, governed data access, and a trail that holds up at an FDA submission. That's a different problem — and it's the one we've been working on.

This showcase is built for scientific IT, pharma R&D architects, heads of research informatics, the people who have to make AI production-ready, not just possible.

We'll show you three things:

• What confident AI looks like for a scientist — a working antibody selection workflow where the model knows the data, maintains state, and produces a decision you can document and defend
• What it looks like for scientific IT to build with that confidence — live demos of scaffolding a data app and building a new instrument schema, both from inside an AI assistant, both deploying directly to Tetra OS
• What makes any of it possible — Bring Your Own Model, governed agentic workflows, full observability and auditability baked into the architecture

Capable AI is a solved problem. Confident AI is what we're here to talk about.nce rules, and evaluation criteria

Two commands to scaffold. Plain English to build. A working QC app running on Tetra OS in an afternoon.

In our August Showcase, TetraScience UX specialist Jenn Medellin walks through how to build a live, working scientific app using our CLI and an AI coding assistant. No prior React experience required.

45 minutes · Live demo + Q&A

[Register now →]

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