Claims & Underwriting Automation
Read, triage, and adjudicate claims and applications at scale — extraction, risk scoring, and policy checks with a human on the exceptions.
The problem
Claims and underwriting are drowning in unstructured documents and manual review. Cycle times are long, decisions are inconsistent, and the volume only grows — but every automated decision has to be defensible to a regulator.
What it includes
The capabilities we build into this solution — engineered for production, not a demo.
Document extraction
Pull structured data from claims, forms, statements, and evidence in any layout.
Risk & eligibility scoring
Score applications and claims against your rules and models, consistently.
Policy & fraud checks
Flag inconsistencies, missing evidence, and fraud signals before payout.
Straight-through where safe
Auto-decide the clean cases; route the rest to an adjuster with context.
Explainability
Every decision carries its reasoning and evidence for audit and appeals.
Core-system integration
Writes into your policy admin / claims platform with a full trail.
How we'd build it
The same method behind everything we ship: de-risked, measured, and in production in one quarter.
Feasibility
We validate the use case on your real data, define the accuracy bar and ROI, and give you an honest go/no-go — usually in weeks.
Build & evaluate
We engineer the system and score it against a labelled set until it clears the bar — quality is a measured number, not a promise.
Deploy
We ship to production, integrated with your systems and behind the right human-approval gates, with monitoring from day one.
Operate & improve
We watch it in production, handle drift, and expand scope as trust builds — feasibility in 6 weeks, production in ~90 days.
What you get
- Automated intake and triage for claims and applications
- Consistent, explainable risk and eligibility decisions
- Straight-through processing for clean cases, humans on exceptions
- An auditable decision trail your risk team can sign off
Production AI we've shipped
We'd build your solution with the same discipline behind these real, in-production engagements — described by sector under NDA.
A production document classifier — 5,000+ documents/month, built to a ≥95% accuracy target and live in 8 weeks.
Read the case studyBank-statement automation across 21 banks with a measured 0.24% transaction-direction error rate.
Read the case studyAI-at-POS recommendations running against live in-store transactions across every location.
Read the case studyWant to scope Claims & Underwriting Automation?
Tell us the use case. We'll come back with a feasibility view and an honest go/no-go — a working prototype in about six weeks.
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Location
Barcelona, Spain • Lisbon, Portugal • Sheridan, WY, USA (incorporation)
Why Choose CONE RED?
- AI R&D lab & venture builder — production systems, not slideware
- Feasibility in 6 weeks, production in ~90 days
- Accuracy measured and evaluated — never invented or guaranteed
- Real engagements across financial services, healthcare & retail
- End-to-end support from strategy to deployment
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