Can Forge Agent Gate be used for refunds instead of trading?

Yes. A refund agent can call Forge Agent Gate before issuing a refund. The gate checks amount, customer policy, duplicate risk, counterparty, and approval threshold, then returns allow, hold, or block with a proof trail.

Does the agent need to send all customer data to Forge?

No. The self-serve pattern is to send the minimal action facts needed to check the mandate, such as action type, amount, counterparty, policy reference, and review threshold. Sensitive operational details can stay in the customer's system.

What is the first thing to try?

Pick one action the agent can take and one rule you do not want it to break. Examples include refunds over a ceiling, payments to a new vendor, procurement above a budget limit, account isolation, or a trade above mandate.

Agent action use cases

The action changes. The control does not.

Forge Agent Gate is not only for trading agents. It is for any AI agent that can take an action someone may need to stop, review, or explain later. Give the agent an API key, set the mandate once, and let the gate decide whether the action is allowed, held for review, or blocked.

Start with one workflow: one agent, one mandate, one small set of gated actions.

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Where the gate fits first.

Refund agents	Gate refunds before they issue. Check amount ceiling, duplicate refund risk, customer tier, policy reference, reason code, and supervisor threshold. Let small refunds clear, hold edge cases, and block out-of-policy refunds.
Payment agents	Gate payments and transfers before money moves. Check amount, counterparty, new-payee status, invoice reference, destination, and approval threshold. Stop the agent before a bad payment becomes a bank problem.
Procurement agents	Gate purchases before an order routes. Check approved vendor, budget code, amount cap, contract reference, and human-review threshold. Keep procurement automation fast without making it unbounded.
Approval agents	Gate approve, reject, discount, credit, or exception decisions. Check role, value, policy, customer impact, and escalation threshold. The agent can move routine work while unusual work goes to a person.
Security agents	Gate isolate, revoke, block, or escalate actions. Check severity, confidence, blast radius, asset class, and approval threshold so response agents do not overreact silently.
Trading agents	Gate orders before they reach a market. Check venue, order size, daily loss, hours, and approval threshold. Trading is the sharp demo because the risk is easy to see, not because the product stops there.

The first test

Do not start with the whole company. Start with the one action that would be painful to unwind.

Pick one agent. The refund bot, the payments agent, the procurement assistant, the security response agent, or the trading bot.
Pick one action. Refund above a ceiling, payment to a new counterparty, purchase above a budget limit, approval over a threshold, or trade above mandate.
Pick one proof question. If this action had to be defended tomorrow, what would you need to show?
Connect the gate. The agent calls Forge before the action executes. Forge returns allow, hold, or block, then writes the proof trail.

The lightweight API shape.

Generic action check shape (synthetic)

POST /v1/agentic/events/evaluate
X-API-Key: fi_...

{
  "agent_id": "support-refund-agent",
  "workflow": "refund_authorization",
  "proposed_action": {
    "type": "refund",
    "amount_usd": 4250,
    "counterparty": "customer_8421",
    "target_system": "billing"
  },
  "mandate_ref": "refund_policy_v4",
  "evidence": [
    "original_charge_id",
    "support_reason_code",
    "customer_tier",
    "duplicate_refund_check"
  ]
}

This is illustrative, not a customer record. The commercial point is simple: the agent does not need a full enterprise rollout to prove the value. One API key can gate one bounded action class and show whether the proof trail is worth expanding.

Search terms people will use before they know our category.

AI agent refund control	When a support agent can issue money, the buyer does not search for "agent accountability." They search for refund controls, approval thresholds, audit trail, and how to stop bad refunds.
AI agent payment approval	When a finance agent can move money, the buyer searches for payment approval, new-vendor controls, counterparty checks, and automated payment governance.
AI procurement agent approval	When a procurement assistant can route a purchase, the buyer searches for vendor approval, purchase-order control, budget threshold, and procurement automation risk.
AI trading bot risk limits	When a trader or builder lets an agent place orders, the buyer searches for order caps, venue whitelist, daily loss limit, kill switch, and trading bot risk controls.
AI agent audit trail	When a team needs to explain what happened later, the buyer searches for audit trail, proof trail, traceability, replay, and evidence for automated decisions.

Start with the action your agent should not be able to take alone.

If the action can cost money, change a customer account, approve a vendor, isolate a system, or trigger a trade, it can run through the Gate first.

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