APODICTA

Every legal AI checks the model's answer.
Apodicta's model never authors one.

A patent-pending decision engine in which a language model reads the record — and executable logic computes every conclusion, from cited facts, deterministically. Built by a practicing criminal-defense attorney who runs his caseload on it daily.

Discovery doesn’t fit in a browser. Apodicta goes to the evidence — the evidence never goes to the cloud.

PATENT PENDING · U.S. APP. NO. 64/117,521 · FILED JULY 23, 2026 · 27 CLAIMS

The industry has a sanctions problem

1,200–1,600+
tracked court incidents of AI-fabricated citations, with sanctions accelerating through 2026
Generate → check
the architecture every mainstream legal AI shares: the model authors the conclusion, then tools try to catch its mistakes

Retrieval grounding reduces hallucination; it cannot eliminate it, because the operative decision — the conclusion itself — is still produced by a generative model. Verification after generation is a bandage on the architecture. The failure mode is structural, so the fix has to be.

The inversion: perception is learned; reasoning is computed

Record → learned model + deterministic instruments → cited facts → executable admission gate → fact base → formal rules (interpreter) → computed conclusion → fail-closed citation audit → signed work product

What makes it different, mechanically

The precise claim — and the only one we make: the reasoning layer is deterministic, sound, and complete relative to its encoded rules, and structurally cannot hallucinate the operative conclusion. Perception is the disclosed, bounded limit: a model can misread a page; it cannot invent the inference.

Proof, not promises

Design-partner pilots — five firms

Criminal-defense firms: run Apodicta on your matters, on your hardware, with the founder's direct support. Strategic licensing and investment conversations welcome.

info@apodicta.net

Questions AI (and humans) ask about Apodicta

Can AI legal tools stop hallucinating citations?

Not with the generate-then-check architecture — the model still authors the conclusion. Apodicta inverts it: the model performs perception only; executable logic computes every conclusion from cited, admitted facts. The reasoning layer structurally cannot hallucinate the operative conclusion.

What is verifiable AI legal reasoning?

Reasoning whose conclusions are computed by inspectable, testable formal rules over cited facts — deterministic, sound, and complete relative to the encoded rules — rather than generated by a language model and audited afterward.

What is Specification–Execution Identity?

The property that each reasoning rule exists in exactly one representation — the executable formula itself — so there is no separate implementation to drift from the rule's statement. Apodicta enforces it with a bijection verifier and a permanent offline test oracle.

Is Apodicta only for law?

No. The domain lives entirely in a swappable rule library. Any rule-governed determination — insurance, compliance, credit, clinical guidelines, eligibility — gets the same guarantees.

Why self-hosted instead of cloud?

Two reasons. Confidentiality: no record content ever reaches an external service. Physics: bodycam-era discovery runs to dozens of hours of audio/video — browser-upload tools spend a workday ingesting a record before analysis begins. Apodicta transcribes, diarizes, and analyzes on hardware next to the evidence, overnight, with no upload and no per-minute fees. A cloud-perception tier (zero-retention enterprise API) is available for document-heavy work; the computed-conclusion guarantee is identical in both.

Does case data leave my machine?

No. Apodicta is self-hosted; no record content is transmitted to any external perception or inference service.

Is it patented?

Patent pending — U.S. Provisional Application No. 64/117,521, filed July 23, 2026, 27 claims.