A submission arrives as a stack of documents and third-party lookups, and an underwriter spends hours gathering data before the real judgment even starts. Our engine reads the submission, pulls the risk factors, and assembles a scored decision packet where every number traces back to the document or data source it came from. Your underwriter reviews and approves. It never binds a policy on its own. We have built this three times in production, and we would build yours the same way: assistive, audit-trailed, and owned by you.
For every submission, someone reads the application, chases property or income records, runs third-party lookups, and keys it all into a spreadsheet or a macro. The gathering eats the day, and the volume you can write is capped by how fast people can assemble files. It is slow, it is inconsistent from underwriter to underwriter, and it does not scale without hiring.
The data-gathering and scoring is assembled automatically, each risk factor traced to its source, so your team writes more submissions per day without more headcount, and an underwriter approves every risk with a full audit trail.
Assistive by design: the engine scores and explains; it never decides the risk and never binds a policy.
Applications, property and income documents, and third-party lookups (geospatial, environmental, financial) are pulled into one workflow from a single entry point, like a property address or an application ID.
Risk factors are extracted and consolidated into a structured profile and a risk score, packaged as a decision packet where every factor traces back to the document or data source behind it, with gaps and exceptions flagged.
The packet lands in a review queue. An underwriter checks the sources, adjusts, and approves or declines. Nothing auto-binds, and every action is logged for a complete audit trail.
Turning messy submissions and third-party lookups into a consistent, scored, sourced profile is the exact job we have shipped. Rated 5.0★ on Clutch.
Three production underwriting builds: an automated property-risk underwriting engine →, an income-assurance underwriting platform →, and an automated green-energy underwriting engine → that syncs results into Salesforce.
Before any build, we prototype your underwriting workflow on synthetic or anonymized submissions and show you the scoring, the source-tracing, the underwriter review load, and the ROI. You get a plan and a number, whether or not you build with us.
1–2 weeks · credited in full toward your build if you move forward.
Book a call to start →No. It is assistive. The engine extracts risk factors, scores the submission, and assembles a decision packet with cited sources. An underwriter reviews and approves or declines every risk. It never sets the final decision on its own and never binds a policy.
We're a senior-led studio with a US office in North Carolina, and we have shipped three production underwriting engines plus compliant systems for US fintech and healthcare clients. Synthetic-data demos let you evaluate the approach with zero exposure of real applicant data, and you work directly with the senior-led team building it.
Each factor in the decision packet links back to the document or third-party source it came from, so an underwriter can verify a number without re-doing the research, and every review action is logged for audit.
Alongside it. Platforms handle policy administration and the standard lines; we build the parts they leave manual, your specialty scoring logic, the third-party data pulls, and the review workflow, integrated with the system you already run and owned by you.
Geospatial, environmental, and financial data providers on the input side, and your policy-admin, CRM (including Salesforce), and rating systems on the output side. We scope the exact integrations and their security requirements in the discovery sprint.
Book a 15-minute call. We'll show an underwriting workflow running on synthetic data, scored and sourced, with a human on the approval. No pitch, no pressure.
Book your call →