insurOS is a read-only data integration platform purpose-built for insurance companies. It ingests data from the systems you already run — policy administration, billing, claims, CRM, submission intake — and delivers a single, unified, historically accurate data foundation.
No rip-and-replace. No migration. No disruption to operations. Subscription service with implementation included.
Policy lives in one system. Claims lives in another. Billing is somewhere else. Premium accounting is a spreadsheet. Reinsurance is a separate database. Submissions might be in email.
Every time someone needs to answer a cross-domain question — what's our loss ratio by program group, how is this producer's book performing, what's our earned premium exposure in a given state — someone has to manually stitch data together. The answer takes days or weeks. It's often wrong. And it's never repeatable.
The typical fix: A data warehouse project. 12–18 months. Millions of dollars. A team of consultants who understand databases but not insurance. The result is usually a rigid model that breaks when the business changes, doesn't handle policy versioning correctly, can't track claims development over time, and gets abandoned within two years.
The insurOS approach: Insurance data integration is a specialized discipline. It requires deep understanding of policy structure, coverage hierarchy, premium lifecycle, claims development, reserve adequacy, reinsurance cessions, program group economics, and earned premium computation. Generic data platforms don't have this knowledge built in. insurOS does.
Insurance companies — whether admitted carriers, surplus lines writers, or MGAs with delegated authority — that need a unified view of their own data.
Connect Power BI, Tableau, or any BI tool your teams already use. Actuaries, underwriters, finance, and operations all query the same foundation.
Time-to-value: 90 days to what typically takes 18 months to build — built by engineers who understand that an endorsement mid-term changes the earned premium schedule.
Talk to us about your dataTechnology companies building vertical software for insurance — claims automation, underwriting workbenches, submission clearinghouses, distribution management, agent portals, policy administration modernization.
The problem: Every InsurTech product needs clean, integrated insurance data as input. But building the data integration layer is not your core competency, not what your investors funded, and not what differentiates your product. Yet every deployment at a new carrier triggers the same painful data onboarding cycle.
Economics: Licensed as an OEM component. Bundle it into your subscription pricing. Every InsurTech deployment becomes an insurOS deployment.
Explore OEM partnershipFirms that win insurance transformation engagements — from global SIs to mid-market consultancies with insurance practices.
The problem: Every insurance modernization program eventually hits the same requirement: integrate data across policy, claims, and billing. This triggers a multi-month workstream staffed by consultants who are strong technologists but not insurance data specialists. Expensive, time-consuming, and produces one-off results that can't be reused.
Economics: Partner license with per-deployment fee. Embed the cost in your program pricing. Differentiated capability that wins competitive bids.
Join the partner programinsurOS is not a generic data platform adapted for insurance. Every table, every relationship, every computation reflects the reality of policy structure, coverage hierarchy, claims development, and reinsurance mechanics.
Computed at the coverage level, by accounting month, automatically adjusted for endorsements, cancellations, audits, and corrections. One number. Reconciled. Trustworthy. The denominator in loss ratios, rate adequacy, Schedule P, and reinsurance bordereau.
Not a snapshot — the full history. Every reserve change, every payment, every recovery, every status transition. What actuaries need for loss development triangles and what finance needs for IBNR estimation.
Auto/trucking: FMCSA safety scores, DOT inspections, CDL compliance. Professional liability: NPDB reporting, consent-to-settle, severity scoring. Architecture supports adding workers' comp, property, and other lines.
Detects and tracks program groups — master policies, branded programs, virtual groupings — and aggregates experience across members. Program-level loss ratios, experience-rated renewals, portfolio management.
Every client runs in their own environment. No shared database, no commingling. Physical isolation, verified independently. Exceeds NAIC Insurance Data Security Model Law requirements.
Connect Power BI, Tableau, Looker — whatever your teams already use. Analytics-ready data, no proprietary interface to learn. Adoption happens naturally.
Read-only integration. Policy administration, claims management, billing — everything keeps running exactly as it does today. Value without organizational disruption.
No hourly billing. No scope negotiations. Platform access, implementation, operations, monitoring, and updates — all included. Predictable economics.
The unified, historically accurate, cross-domain data that insurOS creates is exactly what machine learning models require. Available as expansion tiers for clients ready to move beyond descriptive analytics.
Route new claims to the right adjuster with the right authority level. Predict ultimate severity early using historical development patterns, coverage characteristics, and jurisdiction-specific factors.
Identify suspicious patterns across the party relationship graph — individuals appearing in different roles across claims, address clustering, provider networks, coincident timing. The connected view SIU builds manually.
Connect submission characteristics to actual loss outcomes. Answer: "For submissions that looked like this one, what did the claims experience actually turn out to be?"
Feed actuarial reserving models with complete claims development data — reserve changes over time, payment patterns, recovery trajectories — structured for triangle construction.
Combine earned premium at coverage level with incurred losses, development factors, and exposure characteristics. The integrated dataset pricing actuaries need.
30-minute conversation. No pitch deck. Just your data challenges and whether insurOS solves them.
Schedule a conversationPilot Phase: insurOS is currently in pilot with select clients. Availability is limited.