How we prove it before we ship

We treat "it works" as a machine-proven claim, never a vibe. We pick the base model by measurement, the same discipline we use across the stack. We fine-tune against a held-out, red-first verification gate: the tuned model must pass objective checks it never trained on, and we confirm the checks fail against an empty model first so a green result actually means something. Coverage and verification are attested, not assumed — every claim maps to a re-runnable test. And we keep it local by default so your data stays yours. The one honest trade we always state: fine-tuning is powerful because it is narrow. We scope it, prove it on held-out data, and tell you exactly where the model's competence ends. That honesty is the product.

This is one piece of a larger framework we built and operate in production. The full picture — and how it applies to your business — is in the playbook.

We specialize in healthcare because it is the hardest vertical — strict HIPAA regulation, PHI handling, BAA chains, and zero tolerance for failure. If we can build it for healthcare, we can build it for any industry. We work across verticals.