Verifiable AI
01 / 09

Every AI decision.
Backed by evidence.

Inventory, controls, and human oversight for systems, agents, code, and models— without changing your stack.

1:17 demo below. See how a test is verified

Complete Inventory
Systems, agents, models, and services, along with their respective owners and risk levels.
Controls and Approvals
Risks, assessments, and approvals in a single governance record.
Sealed evidence
Every decision is linked to its context, the person responsible for it, and the evidence supporting it.
Verifiable by third parties
Your auditor or the regulator verifies it without needing an account.
The platform
02 / 09

Different processes.
The same body of evidence.

Each module works on a different object, but they all converge on the same layer of context, responsibility, evidence, and verification.

AI Governance

Systems, Risks, and Decisions.

Inventory of systems, agents, models, and services. Risks, controls, assessments, approvals, evidence, and governance history.

See AI Governance → AI Agent Governance

Govern the agent. Prove the action.

Link identity or authority, policy, action, resource, outcome, and human oversight to verifiable evidence of implementation.

See Verifiable AI Agent Governance → Code Governance

The code is also accountable.

Analyze connected repositories, document changes, dependencies, and declared use of AI, and record the results in the same governance registry.

See Code Governance →
Model Governance · MLOps

Models with context, controls, and approval.

Connect MLflow in read-only mode, review versions and results, run defined checks, and record evidence and approvals without modifying the source system.

MLflow · controls · approval · evidence
ISO Management

Controlled documentation. Identified approvals.

Link the reviews, responsible parties, and current status of your management system (ISO 9001, 14001, 45001, 27001, or other) to the preparation of your audits.

View ISO Management → Evidence · V-Seal® · Verify

What matters can be verified.

Associate a cryptographic fingerprint, context, and provenance with documents and manifests, and enable subsequent verification of their integrity and record.

See how it's verified →
In the real world
03 / 09

Documents.
Code.
Models.
Agents.

Documents

Word · Portal · Desktop

Drafting, revisions, approvals, and supporting documentation related to the asset.

Code

GitHub · GitLab

Technical history, analysis, checks, and evidence associated with commits and versions.

Models

MLflow

Versions, controls, results, approval, and evidence of the model.

Agents

Actions · Tools · APIs

Implementation context, authority, policy, oversight, and results.

Audits
04 / 09

Three audits.
A single governance framework.

Code, models, and agents are audited where they already reside, in read-only mode. Each audit records its systems, controls, evidence, alerts, and approvals in AI Governance. They can be contracted separately, and any one can be the first.

Code audit · GitHubThe code, in context.
  • Glossary and technical history of each branch.
  • Proportion of human and AI-assisted work.
  • Code checks with automatic verification.
  • V-Seal of the commit, including its glossary and history.
MLOps audit · MLflowThe models the company trains.
  • Reading from MLflow without writing to it.
  • Six deterministic controls, without AI.
  • Approval before moving to production.
  • V-Seal of artifacts, data and results.
Agent audit · six platformsThe agents run by the company.
  • Vertex AI, Copilot Studio, Azure AI Foundry, Amazon Bedrock, Agentforce, and ServiceNow.
  • Eight deterministic controls, without AI.
  • One approval per published configuration.
  • V-Seal of the agent configuration.
What They Have in Common
A recordA model, an agent, and an assistant are entries in the same AI inventory.
A fileEvidence, controls, alerts, and approvals all under a single audit trail.
A sealA document, a commit, a model, and an agent are all sealed the same way.
A verificationThe same public page to check them, without an account.
Guided Case Study
05 / 09

A high-risk system, governed from start to finish.

See, step by step, how the system records data, who oversees it, and what evidence is sealed for the audit.

View the case →
How it fits
06 / 09

It doesn't replace your stack.
It connects it with evidence.

Security, identity, GRC, MLOps, and runtime tools continue to do their job. V-PROOF adds a common layer for reconstructing and subsequently demonstrating the governance context of an action.

Layer 01

Identity & Access

Who can take action, and under what authority?

↓
Layer 02

Policy / Runtime / Security

What is authorized, restricted, blocked, or monitored.

↓
Layer 03

Tools · APIs · Models · Data

Where the actual execution takes place.

↓
V-PROOF

Verifiable Evidence Layer

Action + context + responsible party + policy + result + oversight.

↓
Result

Audit · Governance · Assurance

Evidence prepared for internal or third-party review.

Integration
07 / 09

Go where the work is already happening.

The integration is designed around the systems, events, and data capture points that the organization chooses to manage. V-PROOF offers APIs, SDKs, webhooks, and specific integrations depending on the deployment.

Interfaces

Portal · Word · Desktop

Spaces for people and teams who need to work with governance built into the process.

Software

GitHub · GitLab

Connected repositories for analysis, technical history, and code evidence.

Models

MLflow

Reading models, versions, controls, and results.

Enterprise

API · SDK · Webhooks

Integration with corporate processes and systems through defined data capture points.

Current Scope

Synchronization, MLOps controls, and certain evaluations run on demand. Current safeguards operate within V-PROOF flows. Gateway, MCP, and extended discovery capabilities are part of the product’s evolution.

Frequently Asked Questions
08 / 09

Questions people ask us before we get started.

Will it replace my current tools?

No. Security, identity, GRC, and MLOps continue to function as usual. V-PROOF adds a common layer of evidence to what is already happening within them.

Who can verify a test?

Anyone with the V-Seal URL can access the verification portal without needing an account: your auditor, a client, or the regulator.

Can you help me comply with the EU AI Act?

Provide the evidence required to demonstrate compliance: inventory, human supervision, and records. This does not replace legal advice.

What should be audited first?

Code, models, or agents. Audits are contracted separately, on a read-only basis, and any one of them can come first.

How do we get started?

With an exposure assessment: we identify where your AI is and what evidence you need.

V-PROOF
09 / 09

Start by finding out
where your AI is.
We'll help you prove it.

Connect systems, agents, people, code, and models with a single layer of governance and verifiable evidence.