AI TRiSM — the framework behind Independent AI Verification
Two kinds of AI answer for your enterprise now: the AI you deploy — chatbots and assistants you connect for verification — and the public AI engines that represent you to customers. AI TRiSM — Trust, Risk, and Security — is the framework behind how Lawnise verifies them. Trust and Risk are what Lawnise checks today against your approved evidence: whether an answer is accurate, and what the exposure means. Security — the integrity of the AI systems themselves — is the framework's third dimension, addressed by a separately governed capability.
Trust — verifying AI answers against your source of truth
Trust is about whether an AI answer matches what is actually true for your enterprise. For each answer Lawnise collects or you submit for verification — from the AI you connect and the public engines it supports — it checks against your approved reference (rate cards, product disclosures, regulatory filings, public statements) and flags where the answer diverges, with the exact response, its source, and a hash-linked evidence trail. It turns a claim about your brand into something you can verify rather than assume.
Risk — exposure, reputation, and regulatory alignment
When AI answers about your enterprise are wrong, the exposure is real: misstated regulated terms, misrepresented financials, a reputation that drifts in the answers customers actually see. The Risk pillar quantifies that exposure across both surfaces and tracks how it changes over time, and helps your teams organize the evidence in relation to reference points relevant to AI governance — the EU AI Act (legislation), the NIST AI Risk Management Framework (a voluntary framework), and ISO/IEC 42001 (a standard). These are distinct reference points; Lawnise does not determine which apply to you, adjudicate legal compliance, or detect violations automatically.
Security — the integrity of the AI you rely on
Security in AI TRiSM concerns assurance over the behaviour of connected AI systems. Lawnise addresses this dimension through ThreatGuard, an AI security-behaviour assurance capability built as a separately governed part of the platform, which may execute only within an agreed and authorized test scope. Its execution and customer release are currently gated: any activation would require consent, active authorization, an approved rules-of-engagement scope, a defined target, and operator permission. It is not enabled by default, not a threat-intelligence feed, and not a general cyber-monitoring product.
One framework for both surfaces
AI TRiSM is not a slide—it is the framework behind how Lawnise runs Independent AI Verification. Trust and Risk operate today across the AI you deploy and the public AI that represents you: verify each answer Lawnise collects or you submit for verification, and quantify and govern the exposure, with a traceable record for when a regulator, a partner, or a customer asks. Security is the framework's third dimension, held as a separately governed capability.
Frequently Asked Questions about the TRiSM Framework
How the Trust, Risk, and Security pillars work together to verify the AI you deploy and the public AI that represents you.
Understanding the TRiSM Pillars
Operationalizing the Framework
Start with what fits.
Talk to our team about verifying the AI that answers for your enterprise — request access for a scoped engagement, or book a briefing for a working session.
The public-AI side of this work builds on the Lawnise Trust Index methodology, and the framework is operated through the Independent AI Verification Platform.
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.