Quantum Data Vault
Protect confidential records while retaining evidence of their integrity.
HYBRID DEVNET · PUBLIC EVIDENCE LIVEVerifiable infrastructure for value, markets, identity, and operational dataInspect the network
Enterprise AI teams, commerce platforms, and finance operations
Controlled agentic commerce
Connect protected business data, reviewed agent context, and explicit spending-policy checks. Plan one useful AI-assisted operation without handing an agent unrestricted authority.
Connected product workflowWhat may the agent know, propose, and ask to execute?
- Protect the source
- Share reviewed context
- Evaluate the proposed action
The challenge
Useful context is not permission to spend.
An agent can find the right supplier instruction and still propose the wrong payment. Your team needs to control both what the agent learns and what its proposal is allowed to request, without turning a shared document into a wallet permission.
A practical starting point
Connect the products around one operation first. Establish the result your team needs, then test the exceptions—not just the happy path.
See the operational example ↓How the products work together
From the first event to a reviewed outcome.
- 01
Protect the source
Keep private files and memory in Data Vault under their own access and recovery controls. Choose an owner for the source material and its revisions.
- 02
Share reviewed context
Prepare a recipient-safe collection in Agentic Memory Exchange. Approve the content, scope the recipient or workload, and review clarification requests without exposing unrelated source material.
- 03
Evaluate the proposed action
If an agent proposes spending, submit the intent through separately authenticated AI Wallet Control evaluation. Inspect the policy decision and reasons. Any approval, signing, or payment execution requires a separately confirmed route and authority.
Illustrative operational example
A purchasing assistant proposes a supplier payment.
Illustrative evaluation: a procurement team shares approved delivery requirements. An assistant uses that context to propose a payment; the team checks the proposal without sending money.
- Confirm the assistant can read the approved collection but cannot retrieve the private negotiation notes.
- Compare a permitted proposal with an out-of-scope destination or amount using the documented evaluation contract.
- Retain the evaluation reasons for the reviewer. Verify that neither test creates a reservation, signature, or payment.
The useful result
A reviewable proposal informed by permitted context. The team can explain the knowledge boundary and the spending-policy result without confusing either with an executed purchase.
Choose the components you needScoped access Scoped access Decision-only preview Operation-scoped access
Products in this workflow.
Agentic Memory Exchange
Give agents and partners approved context while keeping private sources protected.
AI Wallet Control
Evaluate an agent’s spending proposal without handing it a private key.
Governance & Approvals
Know who reviewed a change, which version they approved, and what still needs authorization.
Start with this guide
Build a controlled agentic-commerce pilot
Connect Data Vault, reviewed agent memory, and AI wallet evaluation in a purchasing-assistant pilot with separate authority and clear acceptance tests.
One useful first evaluation.
Follow the worked example, inspect the current contracts, and use the failure cases and checklist to review your own results.
Read the practical guideScope and prerequisites
Agree the operating conditions.
Start with one reviewed collection, an authorized workload, a wallet binding available for evaluation, and representative test proposals. Confirm each product’s operations and access separately. The current AI Wallet Control public preview supports reads and intent evaluation, not transaction construction, approval, reservation, signing, or broadcast. This is an integration pattern; the products do not automatically pass authority between one another.
Confirm the deployment model, support responsibilities, and commercial terms with the team. This workflow is not a service-level commitment or evidence of production activation.
What the pilot should demonstrate
- The intended recipient can read only the permitted collection and capabilities.
- Unanswered questions and revised answers follow an explicit review step.
- Disallowed proposals return a reviewable decision and do not move funds.
- An allowed evaluation is never displayed as approval, balance reservation, signing, or settlement.
- The team records separate owners for source access, collection publication, policy evaluation, and any future execution integration.
Questions before integration.
Can we start without autonomous payments?
Yes. Scope a context-and-decision pilot: prepare permitted information, evaluate proposed actions, and review the result. No funds need to move.
Does a shared collection grant wallet access?
No. Knowledge publication, recipient access, and wallet-policy evaluation use separate permissions. Each must be explicitly authorized.
Where does human approval fit?
Agree a separate review process and evaluate Governance & Approvals where its documented operations fit. A recorded review does not itself enable payment execution.
What should the first evaluation produce?
Aim for a reviewed context collection, recorded permission tests, allowed and denied evaluation examples, and a list of remaining integration dependencies. Agree scope and deliverables with the team; this page is not a service commitment.