Biotech is the vertical where our method ships. Deterministic engines do the science, the AI plans and explains, and nothing reaches the bench on a number the model invented. Three lines of work, from a product in production to early research.
Same method across all three: deterministic engines produce the numbers, the AI plans and explains, and it abstains rather than fabricate.
What holds across every biotech product we build.
Every quantitative result comes from a deterministic constraint-based engine. The AI plans the work and writes it up; it never invents a value the model did not produce.
Interventions ship ranked, with calibrated confidence and SAFE / CAUTION / LETHAL flags, so a non-viable design never costs you wet-lab time.
When the data cannot support an answer, the system says so and returns nothing, rather than a confident guess a lab would chase.
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.