Insurance
Insurance customers judge a carrier the moment they file a claim. We build claims automation copilots, computer vision damage assessment tools, and fraud detection agents that help carriers process claims faster and more consistently, without asking adjusters to trust a black box.
Claims triage time target
Meridian Insurance claims cycle time reduction
Photo-based damage assessments, every step
WhatmakesAIhardhere
Claims processing is slow and heavily manual
A typical claim passes through intake, documentation review, damage assessment, and payout approval, often with an adjuster manually handling each step. Customers wait days for updates on claims that, with better tooling, could be triaged in hours.
Underwriting risk assessment is inconsistent across teams
Different underwriters can reach different pricing decisions on similar risk profiles, based on experience and judgment that's hard to standardize. That inconsistency creates both pricing leakage and fairness concerns.
Claims fraud is difficult to catch with manual review alone
Staged accidents, inflated damage claims, and duplicate filings are often designed to look legitimate on the surface. Manual review catches obvious cases but misses the subtler patterns that only show up across large volumes of claims data.
Customer service volume spikes strain support teams
Catastrophic weather events and other mass-loss situations produce sudden spikes in claims and customer inquiries that overwhelm call centers, leading to longer hold times exactly when customers are most stressed and need clear answers.
Whatwebuild
Claims automation copilots
We build copilots that pre-fill claims intake forms, cross-reference policy terms automatically, and draft an initial claims summary for adjuster review, cutting manual data entry and letting adjusters focus judgment on the parts of a claim that actually need it.
Computer vision for damage assessment
We build computer vision models that assess vehicle or property damage from customer-submitted photos, providing an initial severity estimate that adjusters verify and finalize, speeding up the early stages of a claim without removing human sign-off.
Claims fraud detection agents
We build agents that score incoming claims against historical fraud patterns and flag anomalies, such as inconsistent documentation or claim clustering, for special investigation unit review, rather than treating every claim as equally likely to be fraudulent.
LLM-powered underwriting document extraction
We use custom LLM integrations to extract structured risk data from applications, inspection reports, and prior policy documents, standardizing the inputs underwriters work from and reducing variance in how risk gets assessed across a team.
Data pipelines for actuarial and pricing models
We design data pipelines that consolidate claims history, policy, and external risk data sources to feed actuarial and pricing models, giving pricing teams a consistent, current dataset rather than periodic manual data pulls.
Howwe'dapproachthis
Commonquestions
No. Every claims automation system we build keeps a licensed adjuster as the approver on any payout decision; the AI accelerates intake, documentation review, and initial damage estimation, but final judgment and sign-off remain with your claims team.