Defines the rules
Governance sets what an agent should be allowed to do, and who is accountable.
Independent Agentic Assurance
Independent Assurance for Consequential AI-Agent Actions
Weaveframe reconstructs agent runs against the business authority and rules in force when they occurred, then independently verifies what actually changed in the system of record.
A scoped look at one consequential workflow — before it becomes infrastructure.
TAX — calculation, filing & remittance
PAYMENTS — treasury, payments & settlement
ENERGY — trading, nominations & settlement
AEROSPACE — maintenance, configuration & supply chain
From agent action to independent evidence
See how Weaveframe reconstructs a consequential agent run against the business authority and rules in force at the time, then checks the result against the system of record.
Governance tells an AI agent what it should do. Assurance proves what it actually did.
Stopping an action and proving an action are different problems. Weaveframe is built for the second.
The system that performs the action should not vouch for the action.
The category
Independent Agentic Assurance
Weaveframe independently reconstructs consequential AI-agent runs against the business authority and rules actually in force when they occurred, then verifies the resulting outcome against authoritative systems of record — without relying on the acting agent platform to vouch for itself.
Determines whether execution is permitted
Runtime controls decide whether an action is allowed to proceed.
Records system activity
Observability records what the system did and observed.
Perform actions and generate their own records
The platform that runs the agent takes the action and keeps its own account of it.
Reconstructs the run, independently
Business authority in force, whether the trajectory stayed inside it, and what the system of record shows. What is Agentic Assurance?
Agentic Assurance explains the same distinction for enterprise buyers. Authorization Continuity asks whether the whole trajectory stayed within the original mandate. The Independent Agentic Assurance white paper sets out the evidence architecture.
Executive white paper
Access the Executive White Paper
Independent Agentic Assurance
Verifying What AI Agents Actually Did
The gap
Logging is not proof.
Agent logs tell us what the platform says happened. Weaveframe establishes whether the business authorized it and whether the authoritative system confirms the result.
What the acting platform can establish
Which agent acted, and with what credentials
Which tools it called
Which policies and runtime controls evaluated the step
What the platform itself recorded
What Weaveframe establishes
Business authority. Was the run inside the mandate, approvals, and rules governing the business?
Full run. Did the whole trajectory stay inside that authority, even when each step was permitted?
Actual outcome. Does the system of record — ERP, ledger, bank, or tax engine — confirm what changed?
The Weaveframe Assurance Framework
Five questions every enterprise must answer.
Identity, permission, and platform policy locate the agent and what it was allowed to do. Assurance is whether the business authority then in force held for the entire run, and whether the system of record confirms the result.
1
IdentityWhich agent acted?
2
AuthorityWhat was it authorized to do?
3
ActionWhat did it actually do?
4
PolicyDid that stay inside the boundaries?
5
EvidenceCan you prove it?
If an enterprise cannot answer those five questions, it does not yet have assurance over its autonomous AI workforce.
Engage Weaveframe
Assess an agentic workflow before it becomes infrastructure
Before you embed AI agents into critical business processes, make sure you’ll be able to prove what they did. Enterprises are operationalizing agents now. If they do that before deciding how actions, authority, policy, continuity and outcomes will be independently evidenced, they may later redesign permissions, workflows, integrations and evidence capture.
Agent Traceability Assessment
You already have security, identity, and governance. What you may not have is an independent reconstruction of one consequential run: the business authority then in force, and whether the system of record confirms the result.
- A scoped look at one consequential workflow
- Whether a reviewer could later reconstruct what the agent did
- Gaps that could force later architectural rework
Why now
The market is already signaling the problem.
Traditional AI governance was built around models, outputs, and human-supervised review. Agentic systems introduce autonomous execution — and regulators, banks, and enterprises are already reacting. These are public signals, not Weaveframe customers.
Independent verification is becoming part of the AI oversight landscape. Weaveframe applies that principle to consequential agent actions in production. See the white paper.
Who we're for
Built for the people accountable when an agent acts.
Weaveframe is built for the leaders who answer for autonomous AI when something goes wrong — not just the teams building the agents.
CIO
CTO
CISO
Chief Risk Officer
Chief Compliance Officer
Internal Audit
AI Governance & Responsible AI
Enterprise Architecture
Business leaders deploying autonomous workflows
Initial focus: regulated, audit-sensitive environments — financial services, insurance, tax, accounting, compliance, and healthcare — and any workflow where autonomous action creates financial, regulatory, operational, or reputational exposure.
Example assurance environments
Where consequential agents are emerging
These are illustrative environments — not four Weaveframe products, and not a list of industries we serve. Each one shows how the same five-question assurance framework applies when an agent takes a consequential action.
Why a third party
A tool built by the same vendor whose agent is under review has an obvious incentive problem.
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01
We don't build or sell agents
Weaveframe checks the agents you already run — we have nothing to gain from grading them generously.
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02
We check against systems we don't control
The reconciliation source is your bank, your ledger, your ERP, or another authoritative system of record — not a log the agent wrote about itself.
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03
The output is built to be handed to someone else
An auditor, an attestation firm, an insurer, or a board — the evidence is structured for a reader who wasn't in the room.
Weaveframe exists to make autonomous enterprise AI provable.
Trust is a claim. Assurance is evidence.
Design partner program
For teams putting consequential agents into production
The Design Partner Program is for organizations actively operationalizing a live agentic workflow and willing to help shape the Weaveframe platform. Most teams should start with an Agent Traceability Assessment.
What that looks like
- A structured look at how your organization answers the five assurance questions today
- Direct input into the Weaveframe framework and what we build next
- A fixed, transparent scope, agreed before we start — no open-ended pilot
Deploying consequential AI agents?
We're selecting a small number of design partners to help define independent AI-agent assurance.