An AI-powered broker platform replaced manual ACORD reading with field extraction at 94% confidence — and gave the operation a live pipeline, carrier hit ratios, and risk scoring across fifty-plus factors.
Commercial insurance brokers run on PDFs and email. Every new submission arrives as a dense ACORD form, and a junior broker spends 3–4 days reading it, retyping fields into a spreadsheet, and chasing carriers one by one. We built an end-to-end broker platform — AI triage, submissions pipeline, carrier markets, analytics — that compresses that work to 30 seconds per submission and gives the team a live operational view of the whole book.
Commercial insurance does not run on software. It runs on PDFs and inbox threads. Every submission arrives as a fourteen-page ACORD application — insured name, NAICS code, revenue by segment, employee counts per location, prior loss runs going back five years, named-perils exposure, schedules of vehicles and properties. A junior broker opens the PDF, opens a spreadsheet next to it, and starts retyping.
Then the broker writes eight or twelve carrier emails, each one slightly different because each carrier wants the data in a different shape. Carriers reply over the next two to seven days — some quote, some decline with one-line reasons, some come back asking for a field the broker missed. A 3-to-4-day cycle, multiplied by dozens of active submissions per broker, multiplied by a team of fifteen.
“Half our workweek was someone retyping numbers from a PDF into a spreadsheet — and we still had to chase fields they missed.”
The compounding failures: transposed numbers in re-typing. Misread NAICS codes producing wrong appetite matches. Carriers rejecting submissions because one field was missing — wasted days. Bind rates dropping on time-sensitive lines because the broker quoted too slow. And junior brokers — licensed, expensive professionals — spending half their workweek doing data entry that a 1995 OCR vendor could in theory have automated.
The director of operations had been writing the RFP in her head for two years. She knew exactly what she needed. The market had nothing that fit.
One operational view replaced the spreadsheet. KPIs update live, AI flags portfolio exposure, and every recent submission is one click from full detail.
Most "insurtech" tooling is built for the carrier side — Duck Creek, Guidewire, the policy-admin giants. The broker side, the team actually triaging incoming submissions, has no purpose-built workflow software. The closest things on the market were thin GPT chatbots glued on top of CRMs, which lacked the field-by-field explainability a licensed broker needs to defend their work.
The brief was specific: AI-driven extraction grafted onto a real broker workflow, with confidence scores surfaced in the UI on every field. No black-box decisions. A broker has to be able to look at any AI output, see why the model scored it the way it did, override the field with one click, and have the audit log record both the original and the override. We took the brief literally — every AI output in the platform is a transparent, explainable, overridable artifact.
Drop an ACORD PDF on the upload zone. Insured name, industry, revenue, employee counts, locations, prior losses extract in under 30 seconds, each field stamped with its confidence score. Brokers see exactly which fields to verify and which to trust.
Industry hazard, prior loss frequency, exposure concentration, coastal and wildfire geography, employee density, premium-to-revenue ratios. Each component scored separately and rolled into a portfolio risk score with the math visible.
New → Triage → Quoting → Quoted → Bound. Filter by line of business, risk band, premium, carrier, age. Click any submission for documents, extracted fields, incoming quotes, and a complete activity timeline.
Live tracking of which carriers quote, which carriers bind, average response time per line of business. Stops the team from wasting submissions on dead-weight markets and surfaces which appetite matches actually convert.
The platform watches the portfolio continuously — flagging hurricane-season exposure in coastal accounts, surfacing cross-sell opportunities by industry segment, alerting brokers when a key carrier's capacity shifts.
Every email, every quote, every state change, every AI override is recorded with timestamp, actor, and old → new diff. E&O-grade audit trail without anyone having to maintain it manually.
MethodologyNumbers are based on the client's internal submission logs. Pre-launch baseline is the manual workflow from the prior quarter; post-launch numbers are platform data from the first 90 days of operation. Median values where applicable. The bind rate uplift is calculated only on submissions where turnaround time previously sat above the carrier's quoting SLA — i.e., where speed was the binding constraint.
Aegis turned my submission triage team from data-entry into actual underwriting partners. We are closing faster, and our junior brokers are finally doing work that requires their licenses — not their typing speed.
Direct API integrations with the major carriers (Travelers, Chubb, AIG) so submissions route end-to-end without email round-trips. Predictive bind scoring — probability of bind per carrier per submission, ranked at intake. A mobile companion for brokers in the field.
Aegis was built for one brokerage. The pattern works for any submission-driven workflow — insurance, mortgage, procurement, legal intake. If your team is spending days on what should take seconds, let's scope it.