Transform messy submission packets into quote ready underwriting files. Reduce administrative overhead and stay audit ready.
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Faster intake to quote process
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Submissions processed daily
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Lift in high-appetite premiums
Forward or upload files
Clean, confident. Sets the foundation with minimal words.
Understand & Enrich
We analyze every document, extract key data, and enrich the submission.
Assemble
Receive a complete, underwriter-ready submission pack.
Experience the Cune Advantage
AI that does the underwriting prep - end to end
A smarter way to grow with Cune AI
Scale underwriting capacity – without scaling headcount
More Quotes. Better Risks. Same Headcount.
Cune AI doesn’t just feel smarter. It moves real numbers: time-to-quote, underwriter capacity, and the quality of premiums you write.
90% faster intake to quote process
Your team handles 3× more submissions per underwriter without longer days or extra headcount, resulting in Faster Quotes and more business.
90% Faster…
More Business
Uplift in high-appetite,
high-quality premiums
Underwriters spend more time on high-appetite risks and avoid poor-fit business earlier, resulting in cleaner books.
Cleaner Books
Successfully Analyzed
Poor-fit business
High-appetite risks
Already done
High-appetite risks
Now takes less time…
Bespoke to your appetite & gets smarter with use
It learns your appetite, language, and patterns, becoming more personalized for your teams over time.
Smarter over use
Appetite
Language
Patterns
Frequently asked questions
Here are answers to the most common things people ask before getting started.
How does Cune learn our underwriting appetite and guidelines?
Cune turns your underwriting guidelines (appetite notes, referral rules, declination triggers, pricing/terms playbooks) into a structured “decision system,” and can also calibrate from your historical decisions where available. When a submission arrives, Cune extracts key fields from every document (apps, SOVs, loss runs, inspections, emails) and evaluates them against your rules—flagging what matters, why it matters, and what to do next. You can adjust rules anytime, and Cune updates outputs instantly.
Will our data be used to train your models?
How is Cune different from a general-purpose LLM? Are you just a wrapper?
Why do AI agents matter in underwriting and how does Cune use them?
How does Cune support auditability, governance, and regulatory expectations?
What does implementation look like and how do you integrate with our workflow?
