Effortless Policy Admin Management

Manual Risk Review to Intelligent Risk Intelligence
Traditional Pre-Quote Vehicle Value Collection
‍In most insurance companies, before a quote is issued, customers are asked to provide a vehicle value or price range through a static form or an agent conversation. Because this value is self-reported and not validated in real time, it can be inconsistent with the actual market,often overstated, unclear, or entered without context.yet it still flows into pricing and eligibility decisions.When the value looks unusual, the case is pushed into a manual review queue. Staff must follow up, request clarification, and reconcile the number with internal pricing rules and market references. This slows the quote journey, increases customer friction, adds operational workload, and introduces pricing risk due to inconsistent or unreliable vehicle value inputs.
LMM-Based Market-Range Validation with Smart Escalation
‍Bernoly redesigns the pre-quote step around real-time validation and structured decisioning. As the user enters their vehicle price range, an LMM checks it against local market signals and regional context, then extracts the closest realistic market range instantly. The system validates the input on the spot and generates a structured report showing the user-entered value, the market-aligned range, and the confidence level so staff can review quickly when needed.If the value falls within an acceptable range, the user passes immediately and the quote continues without delay. If it’s outside the range, only that specific step is escalated to a human reviewer, with an AI-generated summary explaining why it was flagged and what needs verification. This improves accuracy by preventing inflated or inconsistent values from entering pricing, speeds up quoting by eliminating back-and-forth for clean cases, and reduces costs by focusing human effort only on exceptions, boosting efficiency while keeping customers delighted.