Review pipeline
SOURCE
Secure ingestion
Read-only, least-privilege connectors over an encrypted channel
NORMALISE
Extract & structure
Documents, records and transcripts into reviewable objects
EVALUATE
HaloRT review
Every requirement against every record, deterministically
TRIAGE
Route exceptions
Only the cases that need a human judgement
RECORD
Evidence ledger
Immutable, reproducible, examiner-ready
Requirement engine
Your interpretation of the rule — made explicit and versioned.
Regulation is rarely the hard part. The hard part is your firm's specific interpretation of it: which thresholds apply, what counts as adequate evidence, which exceptions are permitted and who signs them off.
IntelCS makes that interpretation a first-class object. Each requirement carries its source citation, its test, its evidence standard and its owner — and every change is versioned, so a finding always points at the rule as it stood on the day.
—Written in human reviewer language, not code
—Versioned with effective dates and change history
—Scoped by product, entity, jurisdiction or channel
—Tested against known cases before it goes live
Requirement · REQ-0148 · v4
Obligation
Affordability evidence must be on file before any limit increase is applied.
Test
exists(income_verification) AND
dated_within(90d, decision_date) AND
reviewer_signoff.role IN {credit_risk, ops_lead}
Scope
Consumer lending
Owner
Credit Risk
Effective
2026-04-01
Last run
18,402 records evaluated · 37 exceptions · 0 unreviewed
Working in it
Automation with a human where it matters.
IntelCS never quietly closes a case that needs judgement. It clears the volume, and points a person to exactly where accountability sits.
Exception queues that explain themselves
Each case arrives with the failing requirement, the extract that triggered it, the rule version and the model's reasoning. Reviewers confirm or overturn — they don't re-investigate from scratch.
Overturns feed back into the rule
When a reviewer disagrees, the disagreement is captured against the requirement — so the interpretation gets tightened once, rather than reviewed repeatedly.
Coverage you can put on a board pack
Per requirement, per entity, per period: what was in scope, what was reviewed, what failed, what's outstanding and what the outcome was.
Retrospective re-runs
Change an interpretation and re-run history against it. Because runs are deterministic, the delta is a real finding — not model drift.
Segregation of duties
Determine exactly who may author a requirement, who may approve it, who may sign off an exception — enforced in the product, evidenced in the ledger.
Fits your existing stack
Findings and cases push into the GRC platform, case manager or ticketing system your teams already work in. IntelCS integrates into your workflow.
Hosting
One boundary. Ours. And nothing beyond it.
IntelCS is delivered as a managed service on IntelCS infrastructure. Your data enters one boundary and stops there — it is never passed to OpenAI, Anthropic, a hosted inference API or any other third party, because every model we run is our own and runs on our own hardware.
Single tenant
Your own isolated instance
Each client gets a dedicated instance with its own storage, its own model runtime and its own encryption keys. No shared inference pool, no co-mingled records, no cross-client anything.
No onward transfer
The chain ends with us
One data processor, one boundary, one register entry. There is no AI sub-processor to assess, no cross-border inference hop, and no vendor behind us with access to your records.
Never used for training
Your data trains nothing
Client records are used to answer your review, and for nothing else — not model training, not tuning, not evaluation, not benchmarking. Retention follows the schedule in your contract and deletion is verifiable.
Residency, retention, encryption, access control and audit rights are all set out in writing before any data moves — and we will go through them with your security and data protection leads directly.
Security & data handling →