Use Cases
Regulated industries where LLM outputs need verification — not just safety checks, but domain-specific compliance with auditable evidence trails.
Compliance verification for banking chatbots and advisory systems
The Problem
Banking chatbots handle customer inquiries about fees, refunds, account terms, and lending products. A single incorrect statement about APR, refund eligibility, or fee waivers can violate TILA, FCRA, or ECOA — exposing the institution to regulatory action.
How Knowly Helps
Knowly extracts each claim from the LLM response and verifies it against structured banking rules. When the chatbot says "We'll process your full refund immediately," each claim is checked independently: Is a refund permitted? For the full amount? Immediately? Each answer is traced to the specific rule section.
Example Rules
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Refunds over $25 require manager approval -
APR disclosures must include all applicable fees (TILA) -
Adverse action notices must cite specific reasons (ECOA)
Coverage verification and claims processing compliance
The Problem
Insurance AI assistants handle coverage inquiries, claims status, and policy explanations. Incorrect coverage statements or missed exclusions create E&O liability. State-mandated processing timelines add regulatory complexity.
How Knowly Helps
Knowly verifies coverage claims against the actual policy document structure — not just semantic similarity, but rule-level compliance. Exclusions, waiting periods, and state-specific requirements are checked as structured rules.
Example Rules
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Pre-existing condition exclusions apply for first 12 months -
Claims acknowledgment within 15 business days (state requirement) -
Covered procedures must match policy schedule exactly
Clinical decision support verification
The Problem
Healthcare AI systems provide clinical decision support, patient education, and administrative assistance. Incorrect medical information can lead to patient harm, malpractice liability, and regulatory violations.
How Knowly Helps
Knowly verifies clinical claims against approved protocols and formulary data. Drug interactions, contraindications, and dosage recommendations are checked as structured rules with severity classifications.
Example Rules
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Drug recommendations must check contraindications database -
Dosage recommendations must match approved formulary -
Clinical pathways must follow institution-approved protocols
Deploying AI in a regulated industry?
Let's talk about what verification looks like for your domain.