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Agents

Five agents.
One job each.
A person decides.

InackGuard's AI agents do the legwork of compliance: they search, read, compare and watch. Each one follows your policy, stops at a finding and hands its work to a person, with every source attached.

The loop

How an agent works

The same six steps for every agent, so every output can be read and checked the same way.

  1. 1

    Your policy

    Sources, strictness, checklists and thresholds come from the policy version in force.

  2. 2

    Search or read

    The agent searches every source in scope, reads the document or runs the rule.

  3. 3

    A finding

    Each finding is scored or quoted, with its source, page or list date.

  4. 4

    It stops

    The agent never decides. Gaps are named; nothing is shown as clear by default.

  5. 5

    A person decides

    The reviewer records an outcome and a reason, with a second reviewer where required.

  6. 6

    Sealed

    Inputs, findings, policy version and decision are fingerprinted into the record.

The five

Meet the agents

01 · Screening agent

Every source, one search.

Searches sanctions and watch lists, public-office exposure, registers, courts and the news in one pass. Every candidate is scored and tiered strong, possible or weak, with the reason; a company is matched as a company, a person as a person.

  • Optional country and date of birth sharpen the score
  • Sources that could not be searched are named
  • One name, a file or an API call
Takes
A name, a file of names or an API call
Does
Searches every source in scope in one pass and tiers each candidate
Hands to a person
Strong and possible matches, each with its reason, source and list date

02 · Monitoring agent

Quiet until something changes.

Screens your list once as a baseline, then compares every list update with your records. You hear only about changes that touch a record, once, and a choice you record is remembered.

  • Baseline first, so old matches are not new alerts
  • One alert per relevant change
  • Email, Slack or Teams, or a signed webhook
Takes
Your list, once
Does
Compares every list update with your records
Hands to a person
One alert per change that touches a record

03 · Document review agent

Reads the document, quotes the page.

Reads contracts, data-processing agreements, NDAs, certificates and policies against a checklist for that document type. Every point is quoted with its page, and any quote not found word for word is dropped.

  • Missing items listed first, with why they matter
  • Risk levels set by the checklist, not the model
  • Document text deleted after 30 days
Takes
A contract, DPA, NDA, certificate or policy
Does
Reads it against the checklist for its type and verifies every quote
Hands to a person
A brief: missing items first, each point quoted with its page

04 · Rules agent

Tests before it alerts.

Runs transaction rules for payment firms: structuring, velocity, pass-through, dormant accounts and more. Each draft is backtested on your own past activity before it can raise an alert.

  • Nothing is created during a backtest
  • Reason and approver on every threshold change
  • Scheduled runs and one-transaction scoring
Takes
Your transactions and draft thresholds
Does
Backtests each rule on the past 90 days, then runs it
Hands to a person
Alerts and cases, with the rule version that raised them

05 · Record agent

Keeps the proof.

Seals every search, finding and decision as it happens and chains each entry to the one before. Replays any past decision against its stored evidence or against today.

  • Exported bundles verify offline
  • Chain re-verified on a schedule
  • Legal hold and logged erasure
Takes
Every search, finding and decision
Does
Fingerprints and chains each entry; replays past decisions
Hands to a person
A bundle your auditor verifies offline

Boundaries

What an agent never does

The limits are part of the product, written into every output and enforced by the platform.

  1. 01

    Decide

    No agent clears a name, approves a vendor, closes a case or files a report.

  2. 02

    Hide a match

    Weak leads are counted and named. Nothing is dropped quietly.

  3. 03

    Invent a source

    A finding without a source and a date does not reach you; a quote not found in your file is removed.

  4. 04

    Read a gap as clear

    A source that was down, excluded or not licensed is named as not searched.

  5. 05

    Learn from your data

    Your names, documents and payments are never used to train a model.

Oversight

Oversight built in

The controls a compliance lead and an examiner expect, on by default.

Approvals

Threshold, policy and list-scope changes need a reason and an approver who is not the proposer.

Second reviewer

Require a second sign-off on escalations or on any case type your policy names.

Workload you can show

Open cases, time to review and outcomes per analyst, exportable for the monthly report.

A full audit log

Every action by a person or an agent, in one exportable log and a feed for your own systems.

Questions

Can an agent clear a name or close a case?

No. Agents stop at a finding. Clearing a name, closing a case, escalating or filing is always done by a person, and the record shows who.

What does an agent do when a source is down?

It records the source as not searched and the output names it. A gap is never shown as clear, and a re-run picks it up when the source returns.

Where is AI used?

In two places only: a model drafts a one-paragraph synopsis of a finished output, and copies quotes out of a document you uploaded for review. A validator checks both against the sources before anyone sees them. Results, match tiers, rule hits and case outcomes come from defined rules and your analysts. An administrator can switch AI off for the whole organisation.

Can we change how an agent behaves?

Yes, within your policy: matching strictness, the sources and lists in scope, rule thresholds with an approver, and who must sign off. Every change is recorded.

Do agents train on our data?

No. Your names, documents and transactions are not used to train any model.

Put the agents on your own names.

A 30-minute walkthrough with a person, on names you choose.