Biotech is where our approach already ships. The hard science is done by proven models, not the AI, so nothing reaches the lab on a number the AI made up. Three projects, from a live product to early research.
Same rule in all three: the numbers come from real science models, the AI explains them, and it says "I don't know" instead of making things up.
What holds across every biotech project we build.
Every number comes from a proven science model. The AI plans the work and writes it up; it never invents a value the model didn't produce.
Suggestions come ranked, with how sure the model is, and a clear flag: safe, risky, or fatal. A design that can't survive never wastes lab time.
When the data can't support an answer, it says so and gives you nothing, instead of a confident guess your team would waste time chasing.
Strain design, the gut microbiome, or something adjacent. Tell us the problem and we'll point you to the right product, or build toward it.