Platform

Independent AI verification.

Your enterprise is accountable for two AI surfaces: the AI you deploy — chatbots, RAG assistants, copilots — and the public AI that represents you — public and public-facing AI systems such as ChatGPT, Gemini, Claude, Perplexity, and AI search surfaces. Lawnise verifies both against your approved evidence and preserves an audit-ready record. Launch scope: banking and insurance in Malaysia and Singapore.

Pillars · 3Surfaces · your AI + public AIEvidence · audit-ready

What we verify

Two AI surfaces now speak for your enterprise.

Lawnise verifies both AI surfaces your enterprise is accountable for. The AI you deploy — chatbots, RAG assistants, copilots — is verified against your approved knowledge through the Internal AI connector, with encrypted transcripts and per-tenant consent. The public AI that represents you — third-party AI answers, AI search results, citation trails, brand rankings, competitor comparisons, and claims attributed to your products — is scanned continuously across the major answer engines. Findings from both flow into one governance workflow for review, evidence preservation, and follow-up.

Third-party AI answers

AI search results

Citation trails

Brand rankings

Competitor comparisons

Claims attributed to products

Fact verification · Pillar 01

Verify what any AI you're accountable for says is true.

Fact verification checks whether an AI answer — the AI you deploy or public AI — matches your approved knowledge (the TruthGuard engine).

It helps teams detect inaccurate answers, contradictions, unsupported claims, stale facts, and risky responses before they become accepted public narratives.

Every flagged answer is tied back to evidence so reviewers can see what was said, what source of truth it was checked against, and why it needs review.

Representation assurance · Pillar 02

Track how public AI represents you.

Representation assurance monitors how your organisation is represented across public AI and AI search surfaces (the BrandGuard engine).

It tracks visibility, Share of Voice, first mentions, recommendations, competitor comparisons, reputation signals, citation sources, and whether AI systems describe the brand using approved or harmful attributes.

This helps regulated teams understand not only whether they appear, but how they are positioned.

Source governance · Pillar 03

Govern the documents any AI may rely on.

Source governance reviews the documents and claims that shape what any AI may rely on, quote, or distort (the SourceGuard engine).

It supports document parsing, PII redaction, compliance review, claim extraction, source alignment, and retention controls for sensitive workflows.

This gives teams a governed way to prepare source material before it becomes part of the wider AI answer ecosystem.

Capability map

What teams can evaluate.

Lawnise gives regulated teams a documented way to evaluate their AI exposure — across the AI they deploy and the public AI about them — over seven dimensions.

#DimensionWhat it evaluatesPillar

C-01

Answer accuracy

Inaccurate answers, contradictions, unsupported claims, stale facts.

TruthGuard

C-02

Visibility

Whether your organisation appears, where it appears, and how prominently.

BrandGuard

C-03

Reputation

Sentiment, harmful associations, risky comparisons, brand perception.

BrandGuard

C-04

Citation trust

Official, partner, third-party, competitor, or untrusted source references.

SourceGuard

C-05

Brand consistency

Whether AI uses approved or harmful attributes.

BrandGuard

C-06

Compliance readiness

Mapped rules, claim review, document-type context, redaction.

SourceGuard

C-07

Evidence readiness

Preserved answers, source context, review decisions, audit trail.

Cross-pillar

How it works

Scattered AI answers become a governed workflow.

Lawnise runs a five-step workflow that turns ad-hoc AI exposure into procurement-grade discipline:

Scan

Scheduled coverage of public AI engines and AI search surfaces.

Verify

Compare each answer against your approved knowledge base.

Classify

Route flagged answers to the right pillar review queue (truth, brand, or source).

Review

Human approval or escalation through workspace queues.

Preserve

Every decision is saved with evidence for procurement audit.

Each step preserves audit-ready evidence so regulated teams can show their working when procurement asks how their AI is verified.

Lawnise's platform operationalises the AI TRiSM for enterprises category, with scoring grounded in a documented research methodology.

Lawnise structures this work across three solution areas — Internal AI Validation for the AI you deploy, External AI Misrepresentation Audit and Monitoring for the public AI that represents you, and AI Security Assessment, currently available for scoping and readiness discussion, for its security-behaviour dimension.

Start with what fits.

Start with a scoped pilot or briefing. Lawnise configures access around your governance surface, markets, and evidence needs.

Request access

Scoped access for regulated teams.

Book Briefing

For procurement teams evaluating Enterprise. 30-minute working session.