Relynt

Approve. Constrain. Audit.

The gateway for AI agent actions.

Authorization gateway for AI

Approve, constrain, and prove every write to production systems, with least-privilege policies, human approvals, and signed receipts.

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  • Least privilege by action
  • Human approvals in Slack
  • Signed receipts for audit

AI agents are powerful.
But power without governance is liability.

Unchecked Agent Actions

AI agents execute write operations directly against production systems. No policy evaluation. No human oversight. No audit trail.

Invisible Risk Exposure

High-value transactions, sensitive data modifications, and irreversible actions happen without visibility into what agents are doing.

Compliance Blind Spots

When regulators ask for proof of authorization and decision lineage, there's no cryptographic evidence to provide.

The Solution

What Relynt does

A policy-first gateway that turns agent intent into controlled, auditable actions.

01

Agent Identity

Identity-first audit trail

Every request is tied to a verifiable agent and instance.

  • Every agent gets a unique identity (agent_id + instance_id)
  • Track which agent instance made each request

02

Authorization & Approvals

Policy → approve → execute

Policy gates run before tools, with human review when needed.

  • Policy-driven access control per action and resource
  • High-risk actions routed to Slack for human approval

03

Signed Action Receipts

Tamper-evident record

Every decision is signed and stored for compliance.

  • HMAC-SHA256 signed receipt for every decision
  • Append-only audit log for compliance
Policy Pipeline
live flow
1
Request
Agent intent + payload
2
Authorize
Policy + approval
3
Execute
Connector + receipt
Sample Requestsigned
{
  "agent_id": "sales-copilot",
  "instance_id": "inst_abc123",
  "action": "update:deal",
  "resource": "crm:deal:456",
  "payload": {
    "stage": "closed_won",
    "amount": 50000
  }
}
How it works

From request to receipt in four steps

A policy-first pipeline that turns agent intent into controlled execution and cryptographic receipts.

1

Agent sends structured request

step 1

The AI agent calls Relynt with a canonical payload: agent identity, action, resource, and optional payload.

Policy signals propagate to the next stage
2

Policy evaluated

step 2

Relynt evaluates the request against your policy rules. Outcome is allow, deny, or pending_approval.

Policy signals propagate to the next stage
3

Approval (optional) in Slack

step 3

When policy requires approval, a message is posted to your Slack channel. Humans approve or deny with one click.

Policy signals propagate to the next stage
4

Execute via connector and write signed receipt

step 4

On allow (or after approval), the connector runs the tool call. A signed receipt is written for every decision.

Policy signals propagate to the next stage
Sample requestsigned receipt
policy: allowapproval: optionalreceipt: hmac
{
  "agent_id": "sales-copilot",
  "instance_id": "inst_abc123",
  "action": "update_deal",
  "resource": "crm:deal:456",
  "payload": {
    "stage": "closed_won",
    "amount": 50000
  }
}

Blog

Insights on policy, security, and building with agents.

Product updates, engineering notes, and policy patterns from the Relynt team.

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Ship agents that can write, without losing control.

Policy-driven authorization, optional human approval in Slack, and a signed receipt for every decision. Get the gateway your AI agents need.

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