IRAH
ENTERPRISE AGENTIC AI

Agents that act.
People in control.

From claim intake to verified service requests, agents can read approved documents, prepare decisions and complete permitted steps while people approve exceptions.

01 / TOOLS & DATA02 / APPROVAL GATES03 / AUDITABLE WORK
TOOLS & APIsConnected actions
DOCUMENTSTrusted knowledge
HUMAN REVIEWControlled decisions
ORCHESTRATIONPlan · Route · Verify
02 / LIVE WORKFLOW MODELMORE THAN A CHATBOT

The decision trail behind every agent action.

Follow a sample insurance claims workflow. Each lane has a separate job: handling evidence, running permitted actions, or asking a human for judgment.

CASE FILE / EXAMPLE ONLY
CLAIM REQUEST
01 — Parse & validate ↗
CONTROLLED ACTIONS

Agent orchestration

Identity checked · tools allowlisted · facts source-linked

Execution log ↗
HUMAN DECISION

Ready for review

Missing evidence flagged. No automated settlement.

Claims journey ↗

Illustrative process; not a connected real-world claims system.

CONTROLLED AUTONOMY

Agents need limits, permissions and a clear handoff.

An agent must know which documents it can access, which tools it can use and when its next action requires a person to approve.

01

Understand

Retrieve permitted knowledge and task context.

02

Plan

Choose a bounded route, tool and success condition.

03

Execute

Use allowlisted tools with identity checks.

04

Verify

Check outputs and escalate consequential decisions.

PILOT METHOD

Judge agents by completed work, not fluent answers.

A successful pilot records task completion, incorrect actions, justified escalations, exception handling and time recovered by the team.

Task completionCorrect outputs against accepted cases
Exception handlingQuality of escalation and fallback
TraceabilityAuditable decisions and tool usage
Operating economicsEnd-to-end effort and latency
A DAY IN THE WORKFLOW

Follow a claim from intake to a reviewer-ready file.

A practical example of bounded automation—not a promise that every task can safely run without people.

01

Receive evidence

Collect a claim packet, identify document types and check whether mandatory information is present. Incomplete submissions are routed back for clarification.

02

Check policy

Retrieve the correct policy rules and compare the evidence against permitted conditions. Missing sources or conflicting data are flagged rather than guessed.

03

Propose and escalate

Produce a review-ready summary with sources, exceptions and next actions. A human reviewer controls consequential decisions and authorised system updates.