Confidently wrong is the real risk.
The dangerous failure is not AI that refuses. It is AI that reads more expert than the truth, and in a regulated setting that is exactly what a reviewer waves through. We build the controls that catch it, before anyone sees the output. Engagements are contracted through Celagenix® Corporate and use Celagenix Digital's tools.
Every model is trained on someone else's law.
A model writing your local content drifts to the patterns it saw most in training, so a system generating South African compliance text reaches for the EU's GDPR clause, not the POPIA one. The wrong answer reads more sophisticated than the right one, which is why a reviewer skimming is reassured by exactly the text that would embarrass them. There are reported cases of courts sanctioning filings that relied on fabricated citations. "AI-generated" is no longer a neutral phrase.
One loop. Four stages.
It runs continuously, not once, because models change under you, sources go stale, and the law moves. Each stage maps to how enterprise AI assurance is actually done: test and evaluate, ground, gate, and monitor.
Expose
- Map the AI surface and its failure classes.
- Test the AI against known-right answers and deliberate traps.
- Score outputs for groundedness and factuality.
- Rank error classes by consequence.
Offer: the Confidence Review
Ground
- Ground the system in authoritative sources.
- Require a real citation for every claim.
- Limit the AI to approved sources: answer from authority, reach nothing it must not.
- Define where the model may and may not point.
Offer: Grounding & Boundary Design
Gate
- Controls that stop output that fails a check.
- Automatic checks that every claim points to a real source.
- Self-correction loops that revise, not ship.
- Run automatically every time anything changes.
Offer: Control Build
Monitor
- Continuous test, evaluation, verification, validation.
- Score live traffic; detect drift.
- A short written position each quarter a committee can minute.
Offer: Standing Assurance
We ship these controls. We don't describe them.
Checked legal content
Checks that catch foreign-law wording and citations that do not exist.
Sign-off bound to the artefact
A narration approval applies only to the exact audio that was checked.
Checks between every stage
A staged production process with a quality check between stages, and clear hand-offs from one stage to the next.
An instruction to verify is not a verification step
From our own products. It is why we build checks that stop output, not prompts that ask nicely.
We name our limits.
A practice that names its own limits is the one a legal gatekeeper trusts. Here is what we will not do, and what we do instead. It is a selling point, not a disclaimer.
Where can your AI be confidently wrong?
Take the Confidence Assessment. Score your exposure across the ways AI output fails in a regulated setting, in minutes. No email required.