Five systems for one decision
The score is in one tool, the screening hit in another, the analyst note in the case system and the approval in an email thread. Pulling them together is manual every time.



28 specialized agentsAll systems operational
Ready to transform your security infrastructure?
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Aiden FluxSenior AI Fraud Risk AnalystFraud Detection & Risk Scoring
Rhea LedgerSenior AI KYC/AML Compliance DirectorKYC/AML & Sanctions Screening
Nova SentinelLead AI Zero Trust Security ArchitectZero Trust Access Security
Iris VermaAI Verification SpecialistIdentity Verification & KYC
Oscar GraySenior AI OSINT Intelligence DirectorOSINT & Threat Intelligence
Bella NovaAI BNPL Risk AnalystBNPL Risk Monitoring


28 specialized agentsAll systems operational
Ready to transform your security infrastructure?
Explore our complete agent library and request a custom demoView All Solutions


28 specialized agentsAll systems operational
Ready to transform your security infrastructure?
Explore our complete agent library and request a custom demoView All Solutions
Arin Narrate — Senior AI Audit Trail SpecialistArin Narrate is an AI agent that links every agent and analyst decision to its evidence and keeps the record tamper-evident. When an examiner or internal auditor asks why a case was closed, he assembles the case file, the audit pack and a draft answer for your team to check before anything goes out.

An examiner picks a sample of closed alerts and asks why each was closed. The answer is split across the monitoring system, the case tool, email and an analyst who has since moved teams. Your team spends the visit rebuilding decisions instead of explaining them.
to rebuild one sample by hand
Examiners ask why each alert closed.
The score is in one tool, the screening hit in another, the analyst note in the case system and the approval in an email thread. Pulling them together is manual every time.
Rules have been retuned and models retrained since the alert closed. Without the version and inputs used at the time, you can't show how the decision was reached.
Three people answer three examiner requests three different ways. Inconsistent answers draw follow-up questions, and follow-up questions draw findings.
Arin Narrate is a Senior AI Audit Trail Specialist. He records what every agent and analyst decided, on what evidence, under which rule and with whose approval, and turns that record into audit packs on request.

We don't publish performance numbers from our own tests. Give Arin Narrate a sample your last examiner asked for and compare his pack with the one your team built.
Arin Narrate reads decision data from your systems through APIs. Your systems of record stay where they are.
Decisions arrive from your monitoring, screening and case systems and from FluxForce agents: the alert, the inputs, the score or rule, the explanation, the outcome and the person who approved it.
Arin ties each decision to the rule version, model version and policy in force at the time, so a decision from last year can be shown as it was made.
The record goes into tamper-evident evidence storage. Corrections are added as new entries, and the original stays visible next to them.
On request, Arin builds the case file or audit pack and drafts answers to the questions asked. A standard pack can go out on its own if you allow it. Examiner answers always go to a person to review first.
Run Arin Narrate in shadow mode against the last sample your examiner requested. He links the evidence and builds the pack, and nothing leaves your team. Compare his pack with the one you sent.
Arin doesn't make you compliant. He keeps the evidence these frameworks expect you to produce on request.
One record per decision. Packs built from it on request.
| CRITERIA | Manual evidence gathering | Case management system logs | Arin Narrate |
|---|---|---|---|
| Time to audit pack | Days of pulling records | Exports, then manual assembly | Assembled on request, reviewed by your team |
| Who signs off | Your team | Your team | Your team, from Arin's draft |
| What the record shows | Whatever analysts saved | Status changes and user IDs | Inputs, rule, model version, explanation and approver |
| Change history | Spreadsheets and email | Depends on the vendor | Tamper-evident, every change logged |
| Covers AI agent decisions | Rarely | Only the final status | Yes, with the explanation behind each one |
| Where it's weaker | Slow and depends on who remembers | Shows what changed, not why | Only as complete as the systems connected to him. Decisions made elsewhere need importing or stay out of the record |
Arin keeps the record. These agents create the decisions and narratives that go into it.

Checks decisions against approved controls, and Arin keeps the evidence for each check.
Meet Zara
Writes case and incident narratives from the evidence Arin links.
Meet Nolan
Adds screening, KYC and customer risk decisions to the record Arin keeps.
Meet RheaLow risk can run on its own if you allow it. Medium risk goes to a person by default. High risk always goes to a person. You set the bands per rule, channel and transaction type.
Turn Arin off without touching the other agents or your core systems. The switch, and who used it, is stamped on the record.
Run Arin on live data with nothing blocked or closed. Compare the calls with your team's before anything changes.
Every decision answers why, in plain English, with the signals and the rule or policy behind it.
Each decision is stored with its inputs, its reasoning and the person who approved it, in tamper-evident evidence storage.
Agents connect beside your systems through APIs. Your core banking, screening and case tools stay where they are.
What we're learning about AML, fraud and the evidence examiners ask for.






Talk to the people who build the agents. We'll answer per capability, yes or no.
An AI audit analyst records each decision with its evidence, then builds audit packs and draft answers when auditors or examiners ask. Arin Narrate links every agent and analyst decision to its inputs, rule, model version and approver, so your team can show how a decision was reached long after it was made.
No. Arin drafts answers and builds packs. A named person on your team reviews them and sends them. A kill switch turns Arin off without touching your other systems, and the existing record stays in place.
Decisions go into tamper-evident evidence storage, so a later change shows up as a new entry next to the original instead of replacing it. We walk your CISO and auditors through the storage design during deployment.
Arin reads your decision data and builds a pack for a past examiner sample, but nothing leaves your team. You compare his pack with the one you sent and decide what to switch on afterwards.
Decision logs from your monitoring, screening and case systems: the alert, inputs, outcome, analyst note, approver and timestamps. Rule and model version history lets him show old decisions as they were made.
No. Your case system stays the place analysts work. Arin reads from it and from your other systems, and keeps a single linked record of each decision across all of them.
FluxForce runs as SaaS, on-premise or hybrid, built on Microsoft Azure. We agree data residency and which components run inside your environment during deployment design, before any data moves.
Run Arin Narrate beside your current process. He works on your live data and records every call, and nothing is blocked, closed or sent until you decide.
Shadow mode results belong to you.
Start with one workflow in shadow mode, then decide how much each agent does on its own.