Deterministic and reproducible
Findings, severity, maturity levels and the sequenced roadmap are computed by rules, not generated. The same evidence produces the same score every time, so the engine can be independently validated.
The moment you say “AI” to a regulated institution, model risk management engages. This page is written for that conversation.
The number that reaches your board is not produced by a language model. It is produced by a deterministic engine that an independent reviewer can re-run and reproduce.
Findings, severity, maturity levels and the sequenced roadmap are computed by rules, not generated. The same evidence produces the same score every time, so the engine can be independently validated.
The model is handed a bounded set of your own evidence and is not permitted to reach outside it. It composes language over facts it was given; it never supplies the facts.
Every statement has to cite the evidence it rests on, and a verification pass checks those citations after generation. Anything that fails is withheld rather than shown.
Answers are composed against an endpoint that retains nothing. If that guarantee is not explicitly confirmed in the configuration, the platform refuses to answer rather than send your estate somewhere that might keep it.
There is no fine-tuning on client data and no cross-client learning. The model is stateless between requests; nothing an answer touched survives it.
A rule extracted from one of your policy documents is a proposal. It never runs until a named reviewer approves it, and the approval records who that was.
Isolation is structural, not a filter someone remembered to apply.
Which subscription a request belongs to is derived from the credential it arrives with. It is not a field in a payload, so it cannot be supplied, spoofed or mistyped into someone else’s data.
Row-level isolation is enabled and forced on every client table, and the service is refused start-up if it is ever configured with a credential that could bypass it.
The credential that can read your estate cannot read the shared knowledge corpus, and the credential that reads the corpus cannot read your estate. The two only meet in memory, for the duration of one answer.
Answers are composed per request and are never written to a shared store. There is no cross-client “learning”, and semantic retrieval stays partitioned by subscription — a shared cross-tenant index would reintroduce exactly the breach this prevents.
A policy document becomes a rule in a restricted, declarative grammar — not free-form code and not free-form queries.
Rules are expressed in an allow-listed vocabulary and compiled into safe, parameterised checks. Nothing outside that vocabulary is representable, which is what makes machine-extracted policy safe to run at all.
Extraction produces a proposal. A named human reviewer approves it before it can execute, and the approval is part of the record.
Where an internal standard and a statutory obligation disagree, the conflict is surfaced with the resolution guidance attached — rather than being silently resolved in favour of whichever ran last.
The question every regulated buyer asks: where does this sit next to my regulatory reporting chain and my GRC tool?
Your GRC tool holds the control framework and the risk register. FluenBox holds the evidence that the data underneath those controls is measured, governed and current — and complements it rather than competing with it.
Your reporting chain produces the submission. FluenBox evidences the data products that submission is built from — per product, per critical data element, on a date.
The catalogue, the quality engine and the orchestrator all keep running and keep their jobs. FluenBox reads from them and measures what they produce.
FluenBox runs fully isolated in your own environment. Nothing is fetched at run time; the regulatory and framework knowledge it reasons over is stored locally and is self-contained.
Single sign-on against your own identity provider, with strict separation between workspaces.
Where a framework is commercially licensed, the platform ships its own synthesis of the structure rather than the licensed text. If you hold a licence, you load that content into your own instance.
Thirty days on one slice of your estate is also thirty days for your second line to test every claim on this page.