Guardyx for Customer Support

Let support agents actually resolve things, without leaking data or promising what you can’t deliver.

The scenario

AI agents are working the front line now. They answer customers, issue refunds and credits, update accounts, and act on a customer’s behalf. Often, they close cases end to end with no human reviewing every ticket.

Approval requested

Held for a human before it runs.

High riskPending

Agent: Support Bot
Tool: STRIPE_CREATE_REFUND

Arguments

{
  "customer": "cus_Q4mX…",
  "amount": 185000,
  "currency": "usd",
  "reason": "requested_by_customer"
}

Policy

A refund over the $500 support limit: approval required.

What can go wrong

A support agent shows one customer another customer’s personal data: that’s a privacy incident with regulatory teeth. It hands out a refund or credit outside policy. It makes a promise it can’t keep (“sure, we’ll waive that fee forever”). Or it does something destructive to the wrong account. Every one of these lands on a real person, in real time.

Who owns this problem

Your Head of Support or CX owns this day-to-day. Your CISO or privacy owner is accountable for keeping customer data from walking out through an automated channel.

What it looks like deployed

Guardyx sits in front of every action a support agent takes. Answering questions and low-risk fixes just flow. Anything sensitive (sharing account data, a refund over a threshold, changing or closing an account, bending a policy) gets checked and held for a human before it happens. It all gets recorded.

Support agent calls a tool. Guardyx checks the action against your policy before it runs: in-policy actions resolve against customer accounts; exceptions hold for approval. Either way the decision is recorded.

Where held actions wait: each one with its risk, its agent, and the call it tried to make.

What you're covering

You get a guarantee that no agent leaks data or gives away the store outside policy. Your team doesn’t have to read every ticket to check. Agents handle the routine volume; a human only sees the cases that carry privacy, money, or promise risk.

How it fits your existing tools

Approvals land in the Guardyx portal, Slack, or email, wherever your support team already works. Every decision is captured as an exportable, auditor-ready evidence pack. You decide what’s sensitive, what the refund limits are, and which actions always need a human. Exceptions are handled cleanly, so customers aren’t left hanging.

The approver sees the agent, the call, and the agent's own reason for it, marked unverified.

Every decision lands in the run record you export as evidence.

Example controls

A quick, plain-language picture of the policy decisions you'd set:

Allow: Answering questions and low-risk resolutions.
Hold for a human: A refund or credit over your threshold, an account change, or a policy exception.
Deny: Disclosing another customer’s data, or a destructive action on the wrong account.

Without Guardyx / With Guardyx

The exposure today, next to the controlled state with Guardyx
Without Guardyx	With Guardyx
A privacy slip or a bad concession lands on a real customer.	Sensitive disclosures and over-threshold refunds are held first.
Agents either play it too safe or quietly overstep.	Routine resolutions flow; risky actions need a human.
Incidents turn up after the fact.	Every allow / hold / deny is logged.

Without: A privacy slip or a bad concession lands on a real customer.
With Guardyx: Sensitive disclosures and over-threshold refunds are held first.
Without: Agents either play it too safe or quietly overstep.
With Guardyx: Routine resolutions flow; risky actions need a human.
Without: Incidents turn up after the fact.
With Guardyx: Every allow / hold / deny is logged.

The routine clears in one move; only the risky calls wait for a person.

See all seven use cases