In a lab, a clinic, or a courtroom, a confident wrong answer costs more than no answer. We build AI that reasons from each field's own models and evidence, and abstains when the evidence runs out.
We build AI products that reason from a field's established models and data. Each is built for one vertical, deeply, rather than one generic tool stretched across all of them. FluxPilot, for metabolic engineering, is in production today. More will follow as the approach proves out.
The substance of every answer comes from the field's own source of truth, a solver, a validated model, or an established body of evidence, not the language model. The model plans the work, writes it up, attaches the sources it used and a confidence estimate, and returns nothing when the data cannot support a conclusion.
FluxPilot is in production today; healthcare, legal, and finance are active research. If that is how you want to build, or use, AI, we should talk.