Independent AI Trust Infrastructure

Monitor, verify, and govern what public AI says about your business.

Covering banking and insurance in Malaysia and Singapore at launch scope.

No credit card. The free plan includes Free 100 AI visibility checks per month.

Public AI is becoming the first thing buyers, regulators, and analysts read about your business.

Public AI engines already shape how customers, regulators, journalists, and partners describe a regulated enterprise — and the institutions named in those answers cannot see, verify, or correct them at scale. The asymmetry is permanent until governed.

Lawnise builds the Public-facing AI governance and evidence infrastructure that closes it.

We call this Enterprise Public AI TRiSM — Trust, Risk, and Security Management for the public AI surfaces regulated enterprises actually face.

Lawnise is the governance layer: continuous detection, three-engine risk scoring, and an immutable evidence ledger that turns every AI answer into a verifiable record.

Monitor what public AI says about you, across the engines that matter.

Lawnise scans the major public AI engines on a published cadence. Every response is captured, deduplicated, context-snapshotted, and routed into the risk pipeline.

Conversational AI engines
API-based scanning of the major conversational AI engines, on a published cadence. Engine-set defined — expanded as engines stabilize, contracted as they retire.
Search-augmented + Live AI surfaces
Live conversational scanners cover surfaces without stable APIs — search-augmented answer panels and live web AI. Same observation schema, same risk pipeline.
Multi-jurisdiction coverage
Launch scope: Malaysia + Singapore. Region-aware prompt sets, locale-specific reference data, sector-specific compliance rule packs.
Continuous + scheduled scans
Scheduled brand-check runs plus event-triggered scans on regulatory or knowledge-base updates. Every observation lands in the response ledger with a replayable context snapshot.

See full engine coverage on the Platform page

Three risk engines on every response.

Every observation runs through three independent risk engines in parallel — accuracy, compliance, and reputation. Findings are recorded, evidence-anchored, and routed to analyst review.

EntryOne observation — AI response captured

ACCURACY

Fact verification

TruthGuard verifies every factual claim against your Brand Knowledge Base. Confidence-scored contradictions, verdict reason codes, replayable input snapshots — facts adjudicated, not guessed.

Outputs → verdict + confidence

COMPLIANCE

Regulatory rule checking

Compliance rule packs detect breach conditions in real time. Logic triggers, mandate failures, section references — every material finding can be escalated into a forensic Truth Packet ready for auditor review.

Outputs → rule pack + section ref

REPUTATION

Sentiment + brand alignment

Reputation analysis scores AI-described sentiment against your brand attributes, competitor mentions, and toxic-entity exposure — flagged before the framing spreads.

Outputs → sentiment + entity flags

VerdictConverged — routed to analyst review & ledger

Evidence infrastructure

Every finding becomes evidence.

Lawnise anchors every risk finding in an immutable Truth Packet — hash-bound, evidence-preserved, and replayable, traceable from AI answer to verdict. This is what regulatory teams export to auditors.

Step 01
AI Answer
Raw response captured from a public AI engine, with a full context snapshot for replay.
response
"The remittance fee at BankCo MY is …"
response_hash
0x4f7d…a21c
Step 02
Claim Extracted
Atomic factual claims pulled from the response and routed to TruthGuard.
claim
BankCo MY remittance fee = X MYR
subject
brand_id · product_line
Step 03
Evidence Bundle
Brand Knowledge Base sources retrieved and hash-bound to the claim.
sources
3 BKB documents · 1 regulator filing
evidence_bundle_hash
0xc315…d80b
Step 04
Risk Verdict
Three engines render verdicts in parallel. Status pill is enum-locked.
verdict
Stale
reason_code
BKB_FRESHNESS_T+90D
Step 05
Truth Packet
Immutable, hash-bound, evidence-preserved, and replayable adjudication record. Audit-ready, exportable.
Truth Packet · finaltp_id · 0x9b02…7f4ehash-bound · superseded-aware

Verdict reason codesenum-locked

Evidence bundle hashSHA-256 chained

Input snapshotreplayable

Lifecycledraft → final → superseded

See the methodology

Know what AI is saying, prove what is wrong, and act before inaccurate answers become customer, regulatory, or reputational risk.

Enterprise Public AI TRiSM.

Lawnise is built for procurement-grade governance — not just monitoring. Audit trails, evidence hashing, compliance rule packs, analyst workflows, and an append-only response ledger. The buyers' security review starts with data handling and ends with audit readiness.

AUDIT-GRADE

Customer data handling is documented.

Lawnise separates customer-side configuration from benchmark reference data, and publishes its data-handling posture for procurement review. Retention modes for SourceGuard document review: full / ephemeral / immediate.

PROCUREMENT-GRADE

Subprocessors + transparency.

The full subprocessor list is public — required by GDPR, MY PDPA, and SG PDPA. The Trust Center publishes data-handling, retention, and incident-response posture. See the full list before you sign.

See the Trust Center

Built for banking and insurance.

The launch scope covers banking and insurance in Malaysia and Singapore. The platform's architecture extends to other regulated sectors — and to public-AI verification beyond financial services — but the Trust Index, sector benchmarks, and reference data are built one wedge at a time. Sector coverage expands when the data and the review discipline catch up, not when the marketing calendar wants it to.

Banking — MY + SG

Buyers, regulators, and journalists ask public AI about your products, your eligibility rules, and your incident history. The answers shape decisions you do not control.

Read the Enterprise Public AI TRiSM for banking coverage plan

Insurance — MY + SG

Customers ask AI what your policies cover, how to claim, and how you compare. Inaccurate answers move quote requests to whichever insurer the AI describes more clearly.

Read the Enterprise Public AI TRiSM for insurance coverage plan

Launch focus: banking and insurance in MY + SG. Additional regulated sectors are sequenced through the roadmap. Ask about the roadmap.

Authority surface

The Lawnise Trust Index.

The Lawnise Trust Index is a public quarterly benchmark of how accurately public AI models describe regulated enterprises. Each release covers a defined sector and jurisdiction, scored under a published methodology, with every score traceable to evidence in the underlying ledger. The Trust Index is the primary public surface of the Independent AI Truth Jurisdiction Infrastructure (InATJI) — Lawnise's long-term doctrine that AI accuracy about real institutions is a measurable public good.

See the Lawnise Trust Index methodology for the full scoring framework.

Methodology, evidence ledger, and right-to-reply policy are public. Coverage expands quarterly per the Trust Index roadmap.

Subscribe — Trust Index releases

Why it matters

Start with what fits.

The free surfaces show what Lawnise sees. Monitor adds volume and cadence. Enterprise adds custom coverage and managed deployment.

Free 100 AI visibility checks per month. No credit card.

Book Briefing

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