Submission intake
Extract exposures, schedules, loss runs, applications, and missing information from a mixed document set.
We build internal AI products that organize submissions, compare coverage, identify gaps, prepare underwriting packages, and assemble client-ready proposals.
We begin with the operating reality, then design the product around the people, decisions, rules, and evidence already in the work.
Extract exposures, schedules, loss runs, applications, and missing information from a mixed document set.
Compare terms, exclusions, limits, deductibles, and endorsements against the client’s requirements.
Create a clean, consistent narrative and evidence package for the markets you select.
Turn quote data and recommendations into a client-ready comparison with a complete audit trail.
Not a standard product you have to work around. A focused operating layer that can connect the tools and data you already use.
Documents, extracted facts, open questions, and ownership in one place.
Structured comparisons that keep licensed professionals in control of judgment.
Reusable appetite, narrative, and quality checks before an account goes to market.
Milestones, changes, remarketing decisions, and client communication without spreadsheet drift.
These are study results, not forecasts for your business. We use them to establish plausibility, then model your ROI from your own volume, time, labor cost, error rate, and throughput.
Average result in a real-world deployment across 5,179 customer-support agents; less-experienced workers saw gains up to 34%.
NBER field study ↗A Harvard/BCG field experiment also found more than 40% higher quality on knowledge-work tasks inside the AI capability frontier.
Harvard Business School / BCG ↗Average firm-level effect in a 2026 BIS/EIB study of more than 12,000 non-financial firms adopting AI with complementary investment.
BIS / EIB study ↗We’ll show you the internal AI product that can simplify it.
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