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Use-case play

AI agent governance platform

AI agents and automations can read, decide, and act — but who approved each action, and can it be undone? Threada makes every agent action a governed WorkItem: default-deny scopes, an approval gate before execution, reversible actions where the system allows, and a full audit trail.

What it is

AI agent governance is the work of letting AI agents and automations operate your systems without handing them unchecked authority. An agent can draft a reply, move a ticket, issue a refund, or update a record — but each of those is a real action with a blast radius, and someone is accountable for whether it should have happened. The work is making every agent-initiated action a governed, attributable unit: scoped to what the agent is actually allowed to do, gated by approval before anything irreversible runs, and recorded so the decision can be reviewed or undone.

Why it gets stuck

  • 01 Agents are wired straight to API keys, so their authority is whatever the token allows — not what the task actually needs.
  • 02 Propose, approve, and execute collapse into one step, so an agent can decide and act in the same breath with no checkpoint.
  • 03 There is no record tying an agent's action to who or what initiated it, under whose delegated authority, and on what evidence.
  • 04 Reversibility is an afterthought: once an action fires, there is no defined way to undo it or even to know that it ran.
  • 05 Policy lives in prompts and code, so the same agent behaves differently across environments and no one can state the rule it followed.
  • 06 When an automated action goes wrong, the audit is a reconstruction from scattered logs rather than a single governed trail.

What good looks like

One exception, on the record — every field accounted for.

REC-01 Exception record
Caller The agent or automation that initiated the action, with its delegated identity
Authority Scoped to no more than an equivalent human or service principal could do
Action type A typed, validated action proposal, not a raw API call
Policy decision Evaluated default-deny against a versioned policy before anything runs
Approval A decision step before execution; the agent cannot approve its own action
Evidence The grounded context the action was based on, cited on the record
Reversibility Executed with idempotency and an undo/rollback path where the operation allows
Audit trail Caller, policy result, approval, and outcome captured as time-stamped events
Governed · on the record

Original proof assets

Concrete sample records make the workflow inspectable: the WorkItem shows the structured unit of work, and the audit export shows the receipt trail.

Sample output

WorkItem JSON

A concrete record showing the request, extracted fields, confidence, risk flags, evidence links, policy version, SLA, and queue state.

{
  "work_item_id": "wi_3f9a2b7c1d",
  "intent": "vendor_security_review",
  "confidence_score": 0.92,
  "risk_flags": ["external_requester"],
  "policy_set_version": 3,
  "status": "WORK_ITEM_STATUS_IN_REVIEW"
}
generation_mode: illustrative_sample · provenance_citation: docs/spec/product.md#design-principles · Synthetic marketing sample; not tenant data · Replace example IDs, domains, roles, and thresholds before use.
Download WorkItem JSON
Sample export

Audit CSV

An exportable event trail tying intake, proposal, approval, and execution back to the same WorkItem.

event_id,occurred_at,action,actor_email,work_item_id,message
evt_1a2b3c4d,2026-06-18T09:12:00Z,CREATED,system@example.com,wi_3f9a2b7c1d,WorkItem created
evt_3c4d5e6f,2026-06-18T09:58:00Z,APPROVED,a.reviewer@example.com,wi_3f9a2b7c1d,Approval granted
evt_5d1e9b3a,2026-06-18T10:03:12Z,EXECUTED,a.reviewer@example.com,wi_3f9a2b7c1d,Executed governed action
generation_mode: illustrative_sample · provenance_citation: docs/spec/product.md#design-principles · Synthetic marketing sample; not tenant data · Replace example IDs, domains, roles, and thresholds before use.
Download audit CSV

How Threada helps

Each move maps to a real platform capability.

  • 01 Each agent or automation action becomes one governed WorkItem with a typed schema and an accountable owner, so a machine-initiated action is tracked the same way as human work instead of running as a side-channel API call. WorkItem
  • 02 Agent authority is evaluated default-deny against a versioned policy at runtime and scoped so an agent can never do more than an equivalent human or service principal, instead of inheriting whatever an API key happens to allow. Policy overlay
  • 03 Propose, approve, and execute stay separate: an agent can propose an action, but a decision step gates execution and the agent cannot approve its own work. DecisionStep
  • 04 Approved actions run as governed actions with idempotency keys and an undo/rollback path where the underlying operation allows, so an automated mistake can be contained rather than discovered later. Action
  • 05 Caller identity, delegation, policy decision, evidence, and outcome are captured as time-stamped events, so every agent action has one reviewable trail instead of a reconstruction from scattered logs. TelemetryEvent / audit trail

A worked example

Illustrative scenario (not a customer story)

A support automation decides to issue a refund to resolve a ticket. Wired directly to a payments API, it would simply fire the call. As a Threada WorkItem, the refund is a typed action proposal evaluated against policy: under the threshold it can execute and record itself; over the threshold the decision step routes to a human approver before anything runs, and the agent cannot approve its own proposal. Whichever path it takes, the caller, the policy result, the evidence, the approval, and the outcome land on one record. This is an illustrative example to show the shape of the work; it is not a real customer, and no metrics are claimed.

Explore the capabilities

WorkItemsEvidenceActionsGlossaryTrust centerIntegrationsFAQ

Common questions

Does Threada let AI agents act on their own?
Only within explicit limits. Agent execution is default-deny and separates propose, approve, and execute — an agent can propose an action, but a decision step gates execution and an agent can never approve its own action. Its authority never exceeds what an equivalent human or service principal could do.
Can an action an agent took be undone?
Where the underlying operation allows it. Governed actions run with idempotency keys and an undo or rollback path when the target system supports one, and every action is recorded — so an automated action can be contained and traced rather than discovered after the fact.
How is this different from giving an agent an API key?
An API key grants whatever the token can do, with no checkpoint and no shared record. Threada makes each agent action a governed WorkItem: scoped by policy, gated by an approval step, grounded in cited evidence, and captured in an audit trail — so authority is bounded and attributable instead of implicit.
Can we see what an agent did and why?
Yes. Each agent action carries its caller identity and delegation, the policy decision, the evidence it was based on, and its outcome as time-stamped events, so a reviewer can reconstruct exactly what ran, under whose authority, and on what basis.

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