Solutions · Internal AI Validation
Independent validation for the AI your enterprise deploys
Your enterprise is accountable for what its own AI says and does. Lawnise validates that AI independently — against your approved evidence — and shows you where it is accurate, where it is not, and the evidence record behind each finding.
The first of two scopes we verify: the AI you deploy, and the public AI that represents you.
The problem
You deployed the AI. You still answer for it.
Deployed assistants, copilots, and answer systems act in your name — to staff, to customers, to regulators. When one is wrong, your enterprise still carries operational, regulatory, and reputational exposure. Operational checks can show that a system ran; by themselves, they may not establish that what it said was accurate, procedurally aligned, and defensible.
What Lawnise validates
Independent verification against your own approved evidence
Lawnise treats your deployed AI as the subject of verification, not a black box to trust. Against the approved evidence and the approved procedural requirements and test cases you configure for the engagement, we validate two things:
01
Factual accuracy
Does the answer match your approved evidence?
02
Procedural adherence
Does it follow the approved procedural requirements configured for the engagement, across the test cases you designate?
Internal AI is a collection and execution mode inside that verification — not a verdict engine that grades itself. The result is evidence-anchored and independent.
What you get
A reviewable evidence record
The reviewable record can include the prompt, the answer, the applicable approved evidence, and a generated finding record; supported findings can also carry reviewer adjudication. You get factual-accuracy and procedural findings you can act on — a reviewable record you can take into internal review, remediation, and assurance discussions.
01
Prompt
02
Answer
03
Applicable approved evidence
04
Generated finding record
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Reviewer adjudication
Reviewer adjudication applies to supported findings.
How the engagement works
A scoped, access-controlled engagement
Internal AI Validation runs as a scoped engagement, available by request — not a self-serve product. We confirm the verification scope with your team first, agree the systems and approved evidence in scope, and run the validation against them. Access is granted to regulated teams after that scope is confirmed.
01
Confirm scope
02
Agree systems & evidence
03
Run validation
Who it's for
Built for the teams accountable for deployed AI
AI governance, model risk, compliance, and the risk owners who have to prove — not assume — that the AI the enterprise runs is accurate against approved evidence and procedurally aligned.
Start with what fits.
Talk to our team about validating the AI you deploy — request access for a scoped engagement, or book a briefing for a working session.
Scoped access for regulated teams — we confirm the verification scope first.