LiLa, Insurance Vertical AI
Meet LiLa, our Insurance Vertical AI which empowers carriers to spend less time on manual work and more time underwriting, adjusting, and writing business.
The Problem
Generic AI doesn't understand insurance data
Underwriting
Generic models can't reliably extract COPE data, parse loss runs, or read a statement of values. Every submission still needs a human to pull the numbers out by hand.
Claims
A generic LLM doesn't know what belongs in a claim file or how to keep an audit trail intact. FNOL intake and claims classification still run through manual review.
Litigation risk
Litigation risk depends on jurisdiction, attorney behavior and injury severity. Generic models summarize claims but cannot reliably predict which cases reach court.
Data and governance
Generic AI has no built-in governance for high-risk models or third-party data sources. Every new feed becomes a manual compliance review before it can be trusted.
The Solution
Our insurance-trained AI removes the manual work
Underwriting
LiLa extracts COPE data, loss runs, and statement of values automatically, turning submission triage from a manual read into a structured intake.
Claims
LiLa reads FNOL documents and claim files the way an adjuster does, keeping the audit trail intact from intake through classification.
Litigation risk mitigation
Generic AI can't predict which claims are headed to court, it can only summarize the file in front of it.
Data and governance
LiLa runs inside the insurer's own environment, so third-party data and high-risk models stay governed from the moment they're connected.
