Marrow provides a compliance layer that connects AI conversational agents to insurers’ pricing and underwriting systems, enabling real‑time, regulated insurance quotes and policy binding. The platform grounds AI‑generated offers in actual pricing data, enforces underwriting and conduct rules during the conversation, maintains an audit trail, and integrates with existing insurer infrastructure without requiring system changes.
Funding
Funding not disclosed
Founders
Product
Problem
Insurance customers increasingly interact with AI conversational agents to ask detailed, natural‑language questions about coverage, but existing retail insurance systems are not designed to handle regulated underwriting, disclosure, and conduct requirements in real time. This creates a risk of non‑compliant quotes, inaccurate information, and audit gaps when AI‑driven interactions lead to policy binding.
Solution
Marrow provides a compliance middleware that sits between AI agents and insurers’ pricing and underwriting platforms. It translates each AI‑driven dialogue into a regulated quote and, when approved, a bound policy, grounding every response in the insurer’s live pricing data. The platform enforces jurisdiction‑specific disclosure, suitability and conduct rules during the conversation, blocks non‑compliant model outputs, and records a complete audit trail of the interaction. Integration requires no changes to the insurer’s core systems, allowing existing infrastructure to be leveraged across any digital channel. Marrow also offers analytics on chat‑to‑quote‑to‑bind funnels, hallucination rates, and data‑accuracy metrics to help insurers monitor and improve AI performance.
Target Audience
Primary customers are insurance carriers and underwriters that offer regulated products (e.g., motor, travel, and property insurance) and need to enable AI‑driven sales or support channels while maintaining compliance.
Features
- Real‑time compliance monitoring that validates disclosures, legal text, and advice boundaries per jurisdiction during the AI conversation
- Output control that grounds AI responses in the insurer’s approved knowledge base and pricing engine, with a full audit log of source data for each interaction
- Seamless API integration that connects to existing pricing and underwriting systems without modifying core platforms
- Conversion analytics dashboard tracking chat‑to‑quote‑to‑bind funnels, hallucination rates, and data‑accuracy, with exportable reports
- Cross‑model consistency scoring to ensure uniform compliance across multiple AI agents and channels