Revenue · MGAs & Specialty P&C
Cut Quote-to-Bind Cycle Time for Surplus Lines
Compress submission-to-quote with extraction, appetite scoring, and underwriter copilots that sit next to binding authority.
Primary search: quote to bind automation insurance MGA
The problem
Brokers shop the market. Slow quotes lose the placement even when your rate is right.
How we ship it
- 01Lock the KPI: hours from complete pack to quote
- 02Automate the pre-underwrite packet
- 03Surface appetite and risk signals beside the binder
- 04Instrument cycle time so leadership sees the lift
Outcome
More binds at the right premium. Less desk time on incomplete files.
KPI: Revenue
Related searches this page covers
- quote to bind automation insurance MGA
- surplus lines underwriting AI
- specialty P&C AI consulting
More MGAs & Specialty P&C workflows
All MGAs & Specialty P&C →Frequently asked questions
Do we have to rip out our policy admin system?
No. We orchestrate against the PAS and the submission inbox you already have. The first mandate is intake, extraction, and scoring, not a core-system replacement.
How is this different from an insurtech platform?
You own the code, the evals, and the models in your cloud. We are not a multi-tenant underwriting workbench. Scoped production in 6–10 weeks, then your team runs it.
How do you scope AI for our industry?
Week-one discovery locks business KPIs—revenue, cost, risk, or cycle time—not model vanity metrics. We map your data sources, compliance constraints, and existing stack, then propose a fixed-scope mandate with acceptance criteria or redirect you to a simpler path.
Do you have experience in our sector?
Proven depth sectors (financial services, federal, real estate, telecom, higher education) reflect production systems we've shipped. Growth and operator verticals (MGAs, credit unions, property management, 3PL, RCM, staffing, licensed iGaming, FFL) are selective mandates where those patterns transfer with industry-specific tuning. Biotech, insurance, and regulated work often runs under NDA.
What do we get at the end of an engagement?
Deployable code in your repos, monitoring and runbooks, documentation your team can operate, and knowledge-transfer sessions. The Production Standard is contracted in writing—no handoff to a junior bench after the sale.
What's the fastest way to start?
Book a discovery call or start with a bounded diagnostic: $2,500 Postgres audit, insurance claims-fraud diagnostic from $7,500, or the free MLOps readiness assessment. Each path surfaces whether AI is the right tool before a larger commitment.
The Production Standard
The Production Standard
Six commitments contracted in writing on every engagement.
01
Deploy or redirect
If AI isn't the right tool, we say so in week one and redirect budget to what will ship. No POC theater.
02
Metrics before models
Business KPIs locked in discovery. Model selection follows the metric, not the hype cycle.
03
Governance from day one
Model cards, access controls, evaluation harnesses, and audit trails, not a compliance bolt-on at go-live.
04
Production artifacts
Deployed code, monitoring dashboards, CI/CD pipelines, and incident runbooks. Not recommendations for someone else to implement.
05
6-week production target
Scoped projects designed for production in 6–10 weeks. Boutiques move; global programs wait for steering committees.
06
Capability transfer
Your team can operate, extend, and maintain what we build. IP and documentation transfer is included, not upsold.
Every scoped project includes a production deliverable checklist signed off before close. If we can't commit to deployable output, we won't take the engagement.
Selective intake · 2026
Your next system shouldship to production.
Agentic development from architecture through deployment, with the Production Standard contracted in writing.