ATōMIC is a local-first reasoning layer for small models. It measures what the model actually knows, abstains when it's unsure, and shows its work — built for teams where a wrong answer costs more than no answer.
The models keep improving and still confabulate. In regulated work that gap isn't theoretical — it's in the case law, the clinical studies, and the examiner's checklist.
The research already named the fix: reward calibrated abstention, not guessing. EU AI Act transparency duties went live Aug 2026; high-risk lands Dec 2027 — so the teams that start now are the ones who'll be ready.
It sits between your model and its answer. Nothing here is a claim the benchmark can't back.
The hallucination-detection vendors are cloud platforms that judge outputs after the model speaks, adding latency and still false-positiving. The small-model labs don't do reliability. The sovereign players don't publish mechanism. Calibrated reasoning, local-first, is the seat nobody's in.
We're pre-product with zero shipped customers, so we don't ask for trust. We publish a benchmark you run yourself, and we label every number by who measured it.
Small models — 8B, shrinking toward ~300M — mean the reasoning happens where your data already lives. No BAA chain to a frontier vendor, no data-processing addendum, no third-country cloud.
Every scenario is grounded in documented harm — not a customer story we don't have yet. This is what ATōMIC is for.
The developer entry point into epistemic reasoning. Open core, runs locally, quickstart in under five minutes — with an honest note on what's in this release and what's next.
Capped at a few partners — ideally one in legal, one in medical, one in financial. Real scarcity, said honestly. The exchange:
ATōMIC reasons over your data, and how that data is organized matters. NOLA works with P3AK, the private-brain data layer from mpressed: encrypted, portable vaults you own outright, organized under the open Data Room Protocol so regulated documents stay structured, sourced, and sovereign on your own hardware. Each layer works alone. Together, they let an auditor trace any answer all the way back to its source.
Our only social proof is the truth: real people, real research, in the open. [Draft — swap in the real team, photos, and bios.]
Run the Calibration Bench on your own data, or apply to build the first deployment in your vertical.