Make AI governance verifiable.
Proveria connects AI claims to the evidence, policies, evaluations, approvals, signatures, and runtime records behind them — creating durable proof packages that teams, customers, and auditors can independently check.
Verified AI Governance Proof
model-release-v1
- Claim
- This AI release met approved governance requirements.
- Evidence set
- Dataset manifest · evaluation report · runtime evidence
- Policy
- AI Release Policy v1.0
- Evaluations
- Safety, quality, and release checks passed
Problem
AI governance still depends on claims people cannot easily verify.
Organizations are being asked to prove what happened across AI systems: what data was used, what was excluded, which evaluations passed, which policies were followed, which tools or agents acted, and who approved deployment or release. Today, that evidence is usually scattered across documents, tickets, storage systems, model cards, RAG traces, spreadsheets, and approval threads.
The result is a trust gap: teams can explain what happened, but they often cannot produce durable proof that another party can independently check.
Why now
The market is moving from “trust us” to “show me.”
Customers want assurance
They need confidence that AI systems were built and released responsibly.
Auditors need evidence
Internal documentation is useful, but it is hard to independently verify after the fact.
Teams need defensibility
Governance evidence needs to survive review, dispute, handoff, and deployment.
What Proveria does
Proveria turns AI governance claims into checkable proof.
Proveria connects AI claims to the evidence behind them: datasets, manifests, evaluations, policies, approvals, signatures, runtime records, and release history. The result is a durable proof package that can be verified before deployment, after deployment, or during audit.
Proof package
A proof package for every AI governance event.
Verified AI Governance Proof
model-release-v1
- Claim
- This AI release met approved governance requirements.
- Evidence set
- Dataset manifest · evaluation report · runtime evidence
- Policy
- AI Release Policy v1.0
- Evaluations
- Safety, quality, and release checks passed
- Approver
- Jane Smith, AI Governance Lead
- Timestamp
- 2026-06-22 14:18 UTC
Early use cases
Built for teams that need AI claims to survive review.
Model release governance
Prove that release requirements were satisfied before a model shipped.
Agent and workflow governance
Record what agents, tools, approvals, and policies shaped an AI workflow and make that evidence checkable later.
RAG and retrieval evidence
Connect corpus, retrieval, and response claims to committed evidence about what content was available and used.
Customer and auditor proof
Give external stakeholders a durable receipt they can independently verify.
Building AI governance workflows that need proof?
We’re talking with teams working on model release governance, agent workflows, RAG applications, runtime verification, customer-facing verification, investment, and advisory support.