Verifiable AI
Agent Governance.
Every agent has boundaries.
Every governed action can leave evidence.
When AI moves beyond simply generating answers and begins to act upon tools, data, and processes, governing the model is no longer enough. The organization needs to be able to demonstrate each action, its authority, its context, and its outcome.
Govern the agent. Prove the action.
In about a minute and a half, see how V-PROOF reads your agents' configuration, applies eight controls without any language model, and seals each configuration with cryptographic proof.
From copilots that respond
to agents that act.
An agent can query a system, select a tool, modify a resource, initiate a workflow, or propose a decision. Each step expands the governance perimeter.
The question is no longer just what content the AI generated. It also matters what it did, why it was able to do it, what limitations were in place, and who intervened.
Generate a response
The focus is on the content produced and its review. A person asks a question, the model answers, and the person makes a decision.
Perform an action
The focus broadens to include identity, authority, policy, resources, intervention, and outcome. The agent decides the next step.
An action cannot be understood without its context.
Agent governance needs a chain of evidence capable of reconstructing the complete path of an execution.
Identity
Which agent or component was involved in the execution?
Authority
What delegated power enabled that intervention?
Policy
What rules and limits were in place at that time?
Action and resource
What operation was performed and on what tool, data or asset.
Context
What version, input, condition, and sequence surrounded the decision?
Supervision
What approval, review, or human intervention was part of the flow?
Result
What the execution produced and how it was linked to its evidence.
Control during execution.
Evidence to prove it.
The execution infrastructure can limit, authorize, block, contain, and monitor an agent while it acts.
V-PROOF adds a complementary layer of verifiable cryptographic evidence to associate the action with its identity, authority, policy, context, oversight, and outcome.
Runtime and security
Applies operational limits and controls while the agent uses tools, data and systems.
Limit · Authorize · Block · Contain · MonitorV-PROOF
It links cryptographic fingerprint, governance context, and execution evidence for traceability and subsequent verification.
Associate · Document · Reconstruct · VerifyComplementary layers: V-PROOF is not presented as a sandbox, firewall, or operational control engine.
A layer of evidence on the system that is already operating.
The agent continues to work with its infrastructure, policies, and corporate systems. V-PROOF is integrated to link verifiable evidence to the defined flow.
Select a component to see its function within the architecture.
From the connected agent
to its governance context.
Link your agents' settings to controls, managers, and verifiable evidence.
V-PROOF collects the configuration of connected agents and links it to their governance record: model, instruction footprint, access, safeguards, and tools. The record reflects the latest synchronization and the information available on the source platform.
1234- 1Demo Agent Deployed for testing on Vertex AI, keyless and read-only
- 2Its model, version, and fingerprintsettings; the instructions remain on the platform
- 3Safeguards and access: filters and access control, as defined by the platform
- 4What it can do: its tools, what it reads, and what can trigger it without supervision
Authentication · access · tools · knowledge · human oversight · safeguards · documentation · publication. Each configuration has its own unique record: an approval applies to that specific configuration, and the V-Seal records it with a trusted timestamp. Anything a platform does not disclose remains “unevaluated”—never “compliant.”
V-PROOF reads from the platform but never writes to it; the instructions and conversations do not leave the platform. Product and brand names belonging to their respective owners are cited to indicate technical compatibility; they do not imply a commercial relationship.
Where an action needs to be able to be explained.
Application patterns for designing an integration. They do not describe connectors or pre-configured deployments.
Development agents
Relate a modification to the agent, instruction, applicable policy, human review, and resulting version.
Operational agents
Document an action on infrastructure or processes along with its authority, sequence, limits and result.
Transactional agents
Associate a proposal or execution with rules, thresholds, approvals, and evidence of the business workflow.
Publishing agents
Link an asset to its sources, instructions, revisions, approvals, and published version.
Service Agents
Reconstruct what information an agent used, what action they took, what supervision existed, and what result it produced.
Add evidence.
Without replacing the stack.
V-PROOF integrates with existing flows and systems via API and SDK. The scope, events, and context that are logged are defined for each use case.
The integration can associate assets, actions, versions, rules, approvals, and results with a cryptographic fingerprint and a record prepared for verification.
{
"agent": "agent_reference",
"authority": "delegated_scope",
"policy": "policy_reference",
"action": "executed_operation",
"resource": "asset_or_system",
"oversight": "approval_reference",
"result": "result_reference"
}Define
Identify actions, controls, and evidence relevant to the case.
Connect
Integrate the agreed flow using API or SDK.
Verify
Check the integrity, chronology, and recorded context.
Conceptual framework. Availability and specific scope depend on the design of each integration.
Govern the agent.
Prove the action.
If your agents can already act on systems, data, or processes, it's time to design how each execution will be demonstrated.