Provable AI Infrastructure

AI decisions
auditors can
verify.

Every AI decision your system makes becomes a cryptographic proof artifact — independently verifiable by regulators, auditors, and enterprise clients. No trust required.

7
Core features
90
Day pilot
3
Spots available
python cli.py verify proof.json
$ python cli.py verify proof_loan_9284.json
────────────────────────────────
loading proof artifact...
checking protocol_hash
checking governance_gate
checking ledger_integrity
checking merkle_root
running tamper_detection
────────────────────────────────
✓ VALID: Proof verified successfully

protocol_hash 7f3a9c2b4d1e...
model_version credit_model_v3.1
governance all policies enforced
tamper_detected false
final_state approved
verifier independent (offline)
────────────────────────────────
$
The problem

Logs are descriptions.
Proof is evidence.

When a regulator demands proof of an AI decision, can you produce cryptographic evidence — or just logs that could have changed?

Traditional AI systems

AI makes decisions. Teams write logs. Models get retrained. When an audit happens months later, evidence is reconstructed from whatever still exists.

  • Logs are mutable — can be altered after the fact
  • Model may have been updated since the decision
  • Auditors must trust your internal records
  • Evidence reconstruction takes days
  • No independent verification possible

Provable AI

Every decision is recorded the moment it fires — not reconstructed later. The proof artifact contains everything needed to independently verify the decision, forever.

  • Cryptographic hash — tamper-evident by design
  • Exact model version captured at decision time
  • Auditors verify independently, no trust required
  • Evidence ready instantly — not days later
  • Works offline, no server access needed
Architecture

Sits after the decision.
Changes nothing.

A developer can have proof artifacts generating in an afternoon. Nothing in your pipeline changes.

Your existing stack Provable AI adds this
AI system Model + input data Decision Model output + policy applied Provable AI layer Deterministic + signed · sits after decision · zero changes Cryptographic ledger entry prev_hash + curr_hash + signature Storage / logs Your existing infrastructure Proof export proof.json python cli.py verify proof.json
Your existing stack
Provable AI layer
Core features

7 features.
One verifiable system.

01

Deterministic Decision Protocols

Workflow specs compile to a deterministic protocol hash. Same spec → same hash across all environments. Proves execution consistency.

02

Governance Enforcement

Controls which models, agents, and policies are approved to execute. Unauthorized versions are blocked at runtime automatically.

03

Cryptographic Execution Ledger

Each decision transition is signed with a hash chain: previous hash + current hash + signature. Tamper-evident by construction.

04

Signed Proof Artifact Export

Every decision exports a signed JSON proof: curl /ledger/<id>/export > proof.json. Contains full evidence chain.

05

Independent Verification CLI

Anyone can run python cli.py verify proof.json offline. No server access required. Proof either verifies or it doesn't.

06

Replay-based Tamper Detection

Reconstruct any execution history and replay it exactly. If the output differs from the recorded proof — tamper detected.

07

Environment Drift Detection

Compare system roots across dev, staging, and production. Detects governance drift before deployment — not after a failed audit.

Decision flow

From AI decision
to verified evidence.

Every decision in your system follows this chain — automatically, at the moment it fires.

STEP 01

AI Decision

Model processes input, produces output via FastAPI server

STEP 02

Governance Enforced

Gate validates approved model + agent + policy version

STEP 03

Ledger Recorded

Signed hash chain entry created and stored

STEP 04

Proof Exported

Signed JSON artifact with full evidence chain

STEP 05

Independently Verified

Anyone runs CLI — no server access needed

$ curl http://localhost:8000/ledger/instance_9284/export > proof.json
$ python cli.py verify proof.json

✓ VALID: Proof verified successfully
protocol_hash 8f2c1a4e9b3d7f...
governance all policies enforced
tamper_detected false
replay_valid true
final_state approved
Who it's for

Built for the people
regulators call first.

Chief Risk Officer / CRO

Head of Risk

When regulators demand reproducible proof of AI decisions, show them cryptographic evidence — not logs that could have changed. SR 11-7, EU AI Act, CFPB ready.

  • Independent verification without server access
  • Deterministic replay of any past decision
  • Regulatory evidence package in seconds
Model Risk / AI Governance

Model Risk Manager

Stop reconstructing validation evidence manually. Every model decision auto-generates its own proof artifact. Environment drift detected before deployment.

  • Governance enforcement at every execution
  • Environment drift detection across dev/prod
  • Immutable model version audit trail
CTO / VP Engineering

AI Engineering Lead

FastAPI server plugs in alongside your existing AI stack. Python CLI for verification. No rearchitecting required. Open source core, commercial license for production.

  • FastAPI server — integrates in hours not months
  • Python CLI for offline verification
  • Full test suite and documentation included
Common questions

Everything you need
to know.

How long does integration take?

+
A developer can have proof artifacts generating in an afternoon. Provable AI sits after your existing AI decisions — nothing changes in your pipeline.
Step 1 pip install + uvicorn server.main:app → 5 min
Step 2 Point your AI output to the API endpoint → 1–2 hrs
Step 3 Test proof export + verify → 30 min
Total: half a day for one developer

Does it change anything in my existing AI pipeline?

+
Nothing changes. Provable AI is a layer that sits after the decision. Your model makes the decision exactly as it does today. Provable AI records and signs what already happened — it doesn't touch your inference pipeline, your model weights, or your existing infrastructure.

Does the verifier need access to our servers?

+
No server access required — ever. The proof artifact is a self-contained signed JSON file. Regulators and auditors run python cli.py verify proof.json entirely offline. The proof either verifies cryptographically or it doesn't.

What regulations does this support?

+
Provable AI is built for teams operating under SR 11-7 (model risk management), EU AI Act high-risk system requirements, and CFPB adverse action explainability obligations. Documentation support included in the pilot.

What happens if a model is updated between decisions?

+
Every proof artifact captures the exact model version at decision time. Unauthorized model versions are blocked at runtime — so the audit trail is always accurate, even across model updates.

Is the source code available?

+
Yes. The full source is available on GitHub under the Zorynex Source-Available License. Production deployment requires a commercial license — contact hanif@zorynex.co.
90-day pilot

3 spots.
This quarter.

We're running a paid 90-day pilot with 3 fintech teams this quarter. Full deployment. Defined outcomes. Direct access to founding team throughout.

  • Full Provable AI infrastructure deployment
  • Integration with your existing AI stack
  • Audit-ready proof artifacts from day one
  • Independent verifier CLI for your compliance team
  • Environment drift detection across all environments
  • SR 11-7, EU AI Act, CFPB documentation support
  • Direct access to founding team throughout pilot

View GitHub repo →

✓ Received. Hanif will reply within 24 hours.