AI Governance
Without the Governance Theater
Prove your systems coherent and compliant against the rules you declare — before they run.
AI Proposes · AYIOS ProvesLand as Proof. Expand as Substrate.
We land as the proof layer over the software you already run. You do not rewrite anything to get value.
Ingest the regulated system you operate today. Prove it against its own declared rules — and watch the unsafe actions, the data leaks, and the impossible records surface, each one pointing back to a rule you can read. Show the regulator a proof, not a promise.
Then expand: author the next system natively into AYIOS, where coherence is guaranteed from the first keystroke instead of discovered at the end. The compliance you encode compounds into a moat — one regulated domain at a time.
The buyer: the Chief Risk Officer and the Chief Information Security Officer — the office that owns the cost of being wrong, where proof already has a budget line.
11 Unsafe Actions. 7 Data Leaks. 28 Impossible Records.
Compiler-surfaced on a real 130-entity regulated wealth-management system, against its own declared rules — before anything ran.
11 actions that could not safely execute. 7 fields leaking personal data unmasked. 28 records that could never legitimately exist. These are defects that "all the tests pass" will never catch — because they are properties of the model's meaning, surfaced by proving the model coherent before anything runs.
The runtime refuses to load a model it cannot prove sound, rather than silently accepting it and corrupting data downstream. Every finding points back to a declared rule you can read.
Documentation Describes. Proof Enforces.
Most governance describes what should happen. AYIOS proves what can.
Enterprise governance today is documentary — policies, procedures, audit checklists, compliance dashboards. All of it describes what should happen. None of it guarantees what does happen.
The runtime does whatever the code says, regardless of what the governance layer documents. That is governance theater: the appearance of control over a stochastic output that was never proven.
AYIOS replaces governance theater with structural proof. Business rules are declared once; a compiler proves the model satisfies them against the rules you declared, before anything runs.
Violations are structured data, not incident reports. Compliance evidence is derived from the model itself — always current, always verifiable, always auditable.
Measured, Not Marketed
Beneath the proof layer, the runtime is built for production. Each dimension below was empirically measured and produces reproducible evidence.
Compilation at Scale
Runtime Under Load
Safe Evolution
Memory Stability
Error Resilience
The remaining 2 dimensions have identified engineering paths — not mysteries. 5 of 7 is honest. The honesty is the credibility.
What We Prove — and What We Don't
The limit is the strength. We state it plainly.
We prove your model coherent and compliant against the rules you declared — complete, consistent, access-correct, and satisfying your declared invariants. And we make those declared rules inspectable, so a regulator can read exactly what was checked.
We do not claim the declared rules are the right rules. Matching them to reality and regulation is the authoring step — and because the substrate is legible, that step is itself auditable. A model can be coherently wrong; we make sure it is never silently wrong.
A Water Infrastructure Platform
5,500+ IoT probes. 370,000 records per day. Production-deployed in critical infrastructure.
364 legacy entities reduced to 42 semantic entities — with higher fidelity. 1,726 scattered business rules consolidated into 48 formally-enforced invariants. Delivered by 1 developer working with AI.
Not a toy demo. A production deployment in critical infrastructure where correctness is not optional.
Schema-Driven Certification
A tool reads your specification, generates tests, and certifies the deployment. Exit 0 = certified.
The certification tool reads a compiled specification and generates acceptance tests from the schema itself — CRUD coverage, invariant enforcement, workflow transitions, composition integrity. Then it runs those tests against the deployed application via HTTP.
No manual test authoring. The specification IS the test oracle.
$ ayios-certify --model your-system --target https://your-deployment
Reads the model. Generates tests. Runs them. Reports structured findings. Exit 0 = certified.
Your AI Can Evaluate This
Point your AI at /llms.txt — a structured summary it can read without scheduling a demo.
AYIOS publishes a structured, machine-readable platform summary. Your AI evaluator can assess the platform autonomously — capability coverage, diagnostic quality, limitations — without scheduling a demo or reading marketing material.
Evaluate AYIOS
See the enterprise confidence framework in action.