Runtime approval
for AI agents.

Ledgix sits between your agents and the actions they take. Before an agent sends a regulated message, updates a record, touches sensitive data, triggers a workflow, or calls a tool, Ledgix decides whether to allow it, block it, or route it for human review.

Your agents are ready to act.
Your business is not ready to approve them.

Agents are moving from chat into real workflows: payments, customer records, PHI, claims, legal outputs, HR decisions, security changes, and regulated communications.

The blocker is no longer whether the agent works. It is whether legal, security, compliance, risk, and operations can approve what the agent is allowed to do.

01 · RUNTIME

Agents can act before approval

Agents can send messages, update systems, trigger workflows, or call tools before anyone confirms whether the action is allowed or needs human review.

02 · DEPLOYMENT

Production reviews stall

Security and compliance teams slow down deployments because they cannot see which actions are allowed, which need review, and which should be blocked.

03 · OBSERVABILITY

Logs are too late

Logs tell you what happened after the agent acted. Ledgix controls the action before it happens.

Allow. Block. Escalate.
Before the agent acts.

Ledgix sits in the action path of your AI agents. When an agent attempts a sensitive action, Ledgix checks your rules, evaluates the context, and decides what happens next.

Allow

The action matches policy and can proceed.

Block

The action is outside scope, too risky, or not allowed.

Escalate

A human needs to approve before the agent continues.

Review trail

The decision is saved after enforcement.

Fast runtime control. Proof for production.

<0ms
Median latency
p50 clearance end-to-end. Policy eval, A-JWT signing, ledger write.
0lines
To integrate
pip install ledgix · import · wrap. Your agent doesn't change.
0%
Deterministic
Rule engine, not an LLM. Same input → same decision, every time

Why now

Agents are moving faster than approval processes.

Several weeks

Manual security reviews can add several weeks to AI application deployment.

Source: AWS/Cisco

11%

Only 11% of agentic AI use cases reached production in the last year.

Source: Camunda

14.4%

Only 14.4% of organizations have full IT/security approval for their entire AI-agent fleet.

Source: Gravitee

97%

97% of organizations with AI-related incidents lacked proper AI access controls.

Source: IBM

Where Ledgix fits.

Finance

Finance

Approve agent actions around fraud, AML, onboarding, refunds, payments, and customer records.

Healthcare

Healthcare

Control agent access to PHI, clinical intake, patient messages, pharmacy workflows, and provider-reviewed outputs.

Insurance

Insurance

Approve claims, underwriting support, fraud escalation, policy changes, and customer-facing communications.

Legal

Legal

Route contract redlines, legal self-service, M&A review, and compliance outputs for human approval.

HR

HR

Control candidate screening, assessments, employee records, and workforce decisions before agents influence outcomes.

Cybersecurity

Cybersecurity

Approve remediation, access changes, credential actions, and incident-response workflows before agents affect production.

Security tools detect risk.
Ledgix approves action.

Runtime security tools help detect unsafe or malicious agent behavior. Ledgix focuses on the business decision: should this agent be allowed to take this action, in this workflow, right now?

Detect risk

Runtime security tools

Answer: Is this malicious or unsafe?

Detect prompt injection, data leakage, malicious tool use, and unsafe behavior.

Observe after

Observability tools

Answer: What happened after the agent ran?

Show what agents did after the fact.

Approve before

Ledgix

Answer: Should this business action be allowed right now?

Decides whether the agent action should happen before it executes.

Active enforcement.
Not passive observation.

Ledgix does not wait for an incident report. It sits in the live execution path and makes a decision while the agent is trying to act.

AGENTAPI01INTERCEPTSDK middlewarecatches the call02VALIDATEJudge checks intentagainst policies03AUTHORIZEA-JWT issued,scope + expiry bound04EXECUTEDownstream call firesunder scoped token05RECORDTLO signed & chainedinto the ledgercallapprovedHUMAN REVIEWif needed
  1. 01

    Intercept

    SDK middleware stops the outbound call before your integration runs.

  2. 02

    Validate

    The Judge checks intent against live
    policy: approve, deny, or escalate.

  3. 03

    Authorize

    A short-lived A-JWT scopes this action only. The next section unpacks the payload.

  4. 04

    Execute

    The API call runs under that token.
    Nothing broader, nothing stale.

  5. 05

    Record

    Each approved call appends a TLO to your signed, Merkle-chained ledger.

When security asks what the agent can do,
you have an answer before launch.

Enterprises are blocking agents because no one can clearly define what the agent is allowed to do in production. Ledgix gives security, legal, compliance, risk, and operations a runtime approval layer for agent actions before they touch real workflows.

Ledgix helps enterprises say yes to agents without giving them unlimited authority.

  • Define which actions agents can take.
  • Require human approval for high-risk steps.
  • Block actions outside scope.
  • Give teams a clear path from pilot to production.

Your agent should not act
before your business can approve it.

Book a 30-minute walkthrough. We'll show how Ledgix sits between your agents and sensitive actions, how policies decide allow/block/escalate, and how human review fits into the workflow.