Independently verify what your AI agent actually did.
One live, cross-system workflow. We reconstruct one real agent run against the business authority and rules in force at the time, compare what the platform reported with the system of record, and identify where independent proof breaks.
One workflow · 8–10 weeks · Founder-led
- Identity
- Accounts Payable Agent · v2.4
- Authority
- Delegated by AP Manager · limit $100,000
- Action
- Submit vendor payment · $84,200
- Policy
- Payments Policy v3.2 (in force 2026-07-01)
- Approval
- Not required below limit
- Evidence
- ERP payment record matched · Bank file matched
- Result
- PASS
Agents act. Someone else has to trust the result.
Teams deploying agents already have logs, traces, guardrails, and governance policies, and those tools do their jobs. The harder question usually comes later, from someone who didn't build the agent: a risk committee, an internal auditor, a customer, or a regulator.
They want to know whether a specific action was authorized, which policy and approvals applied at that moment, and whether the system of record actually ended up in the state the agent reported. Answering that often means engineers rebuilding events across systems by hand. Native logs and internal evidence may still leave an independent reviewer asking whether the authority, applicable policy, approvals, action, and final outcome can be reconstructed across systems.
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Authority
Was the agent permitted to take this action, for whom, at that time?
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Policy & approvals
Which rules applied, which version was in force, and were required approvals present?
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Outcome
Does the downstream system of record match what the agent reported?
Governance tells an AI agent what it should do. Assurance proves what it actually did.
Built for teams with one agent workflow that matters
This program is for companies actively putting consequential agents into production — organizations with at least one consequential agent workflow that is live or close to it. If you need a first, scoped look at one workflow before a longer engagement, start with the Agent Traceability Assessment.
Good fit if:
- Your agent takes or prepares actions with financial, legal, customer, or operational consequences, such as payments, approvals, filings, account changes, or access changes.
- The workflow is in production or expected to go live within about a quarter.
- Someone outside the building team (risk, internal audit, compliance, a customer, or a regulator) needs to trust the outcome.
- Authority and policy are written down somewhere: delegations, approval matrices, policies, or runbooks, even if imperfect.
- A named business owner and engineering lead can commit time.
Typical participants
If you build agents for enterprise customers, this is how you give their reviewers evidence they can rely on.
If your agents are still in exploration, or every output is reviewed by a human before anything happens, it's probably too early.
One bounded workflow, about 8–10 weeks
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Scope.
Weeks 1–2
Select one consequential workflow and one real run. Bind it to the authority, policy, and approvals in force then. Name the system of record that can confirm the outcome.
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Capture and reconcile.
Weeks 2–5
Connect to agent events and the relevant records using permitted representative data. Reconcile what the agent reports against independent sources.
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Independent checks.
Weeks 4–8
Run checks for authority, policy version, approvals, and downstream state. Surface exceptions along with the evidence behind each one.
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Review and readout.
Weeks 8–10
Walk through the evidence with the people who would have to rely on it. Document what held, what didn't, and what production assurance would require.
- Scope
- one workflow
- Duration
- ~8–10 weeks
- Paid design engagement
- Leadership
- founder-led throughout
Evidence you can hand to someone else
For the workflow
- Independent evidence records. For each material agent action: which agent acted, under what authority, what it did, which policy version and approvals applied, and what the outcome was.
- Exception reporting. Actions where authority, policy, approvals, or outcome didn't line up, with the supporting evidence.
- Reviewer-oriented evidence. Structured so that audit, risk, or a customer can follow it without an engineer in the room.
- Readout. Findings, observed control gaps, and a path to production assurance.
For the partnership
- Product influence. Direct input into what Weaveframe builds, through regular working sessions with the founder.
- Early access to new capabilities as they ship.
- Favorable future commercial terms if you continue to production.
A real workflow and the people who own it
- A product or business owner accountable for the workflow and its outcomes.
- Engineering participation to connect agent events and the relevant records.
- Permitted representative data (production, masked, or representative) within your data policies.
- Authority and policy records such as delegations, approval matrices, policies, and runbooks.
- Regular feedback through scheduled working sessions [confirm cadence, e.g. every two weeks].
Clear boundaries
- Not a replacement for governance, security, or observability tools. Weaveframe works alongside them and uses what they already record.
- Not an agent builder or orchestration platform.
- Not an audit opinion, certification, or legal attestation.
- Not a free pilot. It is a paid, scoped design engagement.
- Not an enterprise-wide rollout. One workflow, done properly.
- Not an equity or IP arrangement. Partners receive no equity in Weaveframe and no ownership of Weaveframe IP.
Talk to the founder
We are taking on a small number of design partners. If you have a consequential agent workflow and someone who will need to trust what it does, let's talk.
The first conversation is 30 minutes with me: your workflow, who needs to rely on it, and whether a partnership makes sense. No deck required.
Jon Odalen, Founder, Weaveframe
Thanks, we've got it. I'll reply personally within [2 business days]. [Founder first name]