Action control for AI agents
Let agents act.
On your terms.
Your agents can move fast. Your business rules should hold. Gatewise checks every proposed action before it reaches your tools.
Early access. One API. Your rules.
The missing check
Tool access is only
half the story.
An agent may have permission to issue refunds. That does not mean every refund should go through.
Amount, customer state and business policy matter. Gatewise checks them at the moment of action.
Meet the action control layerFrom intent to action
One action.
A clear decision.
- 01
Propose an action
Your agent sends the action and its context to Gatewise before calling the business tool.
- 02
Check the rules
Gatewise checks trusted evidence against your thresholds, approval rules and duplicate checks.
- 03
Return a decision
Your application receives an outcome, the evidence and a clear reason. It proceeds only when policy allows.
Issue a refund
- Invoice paid
- Verified
- Customer identity
- Verified
- Previous refund
- None
Above $100. A manager must approve.
Where it matters
Real actions.
Real consequences.
Put a clear boundary around the actions that move money, change records or reach customers.
Refunds
Control autonomous refunds using transaction state, customer data and monetary thresholds. Gatewise decides whether a refund may be issued before the payment tool is called.
02Discounts
Enforce discount limits and route exceptions for approval. Gatewise checks deal size, margin rules and prior concessions before a discount is applied.
03Customer communication
Prevent duplicate, inappropriate or unauthorized customer outreach. Gatewise checks contact state, consent and recent history before a message leaves your systems.
04CRM changes
Control record updates, ownership changes, lifecycle changes and destructive actions. Gatewise separates safe enrichment from changes that move revenue data.
05Contracts and renewals
Verify timing, ownership and business rules before renewal related actions are executed. Contract terms are precise, so the controls around them should be too.
06Finance workflows
Apply deterministic evidence and approval rules before financially sensitive actions. Payouts, credits and write-offs get the same treatment as human initiated finance work.
Start in shadow mode
See the decisions.
Then set the boundary.
Evaluate real agent traffic before enabling enforcement. Learn which actions would pass, pause or stop, and tune your policies with evidence.
Plan your rollout- 01
Observe
Evaluate actions while your existing workflow continues.
- 02
Refine
Review decisions and adjust rules with your team.
- 03
Enforce
Enable control when you are ready, one action type at a time.
The control field guide
Build the right boundaries.
A few clear answers
Where Gatewise fits.
What is AI agent action control?
AI agent action control is a layer between an AI agent and the tools it uses. It evaluates proposed actions against deterministic business policies and trusted system data before allowing, blocking or escalating the action.
How is action control different from AI agent authorization?
Authorization defines which actions an identity may perform and can include contextual rules. Gatewise focuses on the business conditions of a proposed action: evidence, thresholds, duplicates and human approval before execution.
What is the difference between AI observability and AI action control?
Observability tells you what an agent did after the fact. Action control decides what an agent is allowed to do before the action reaches your business systems. The two are complementary, but only one can stop a wrong action.
Controlled autonomy
Move faster.
Keep the final say.
Make business rules part of every agent action.