insurOS is a data platform purpose-built for insurance companies. It connects to the systems you already run — policy administration, billing, claims, submissions — and delivers a single, unified, historically accurate data foundation.
No rip-and-replace. No migration. No disruption to operations. Your source systems stay exactly as they are — insurOS reads from them, never writes.
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, how is this producer's book performing, what's our earned premium exposure in Florida — someone has to manually pull data from three systems and stitch it together. The answer takes days. It's often wrong. And it can't be repeated.
The typical solution: Build a custom data warehouse. 12–18 months. Significant investment. A team of consultants who understand databases but not insurance. The result is usually a rigid system that breaks when the business changes, doesn't handle mid-term endorsements correctly, and gets abandoned within two years.
The insurOS approach: Insurance data integration is a specialized discipline. It requires understanding policy structure, coverage hierarchy, premium lifecycle, claims development, reinsurance mechanics, and earned premium computation. Generic platforms don't have this built in. insurOS does.
insurOS includes purpose-built data models for each major line of business. Not generic schemas adapted for insurance — structures designed around how each line actually works. Programs and MGA books are first-class entities, with dedicated tracking for program-level performance, commission structures, and experience monitoring.
Vehicles, drivers, coverages, and incidents. Driver assignment tracking. Multi-car households with shared drivers.
Dwelling, other structures, personal property, loss of use. Scheduled items. Replacement cost vs. ACV.
Buildings, business personal property, business income. Location-level coverage and limits. Coinsurance tracking.
Occurrence and claims-made coverage. Products/completed operations. Per-occurrence and aggregate limits.
Multi-line policies with property and liability components. Coverage-level premium allocation even on bundled forms.
Scheduled equipment, contractors' tools, builders' risk, installation floaters. Mobile and fixed property.
Fleet vehicles, hired and non-owned, motor carrier coverage. Radius class, vehicle type, driver MVR tracking.
Non-trucking liability (bobtail), trailer interchange, garagekeepers, dealer open lot. The coverages that make trucking and dealer books different.
Cargo coverage for truckers. Commodity class, refrigeration breakdown, theft from unattended, USDOT number tracking.
Claims-made with extended reporting. Practice type, revenue bands, prior acts coverage.
Practitioner credentialing, specialty hierarchy, hospital privileges, consent-to-settle provisions.
Side A, B, and C coverage. Entity vs. individual protection. Securities claims tracking.
Third-party and employee claims. Wrongful termination, discrimination, harassment coverage.
Class code payroll, experience modification, state-specific rating. Injury tracking. Return-to-work programs.
First-party and third-party coverage. Breach response, business interruption, network security, regulatory defense.
Site-specific environmental coverage. Cleanup costs, third-party claims, transportation coverage.
Layered tower structures. Schedule of underlying. Attachment points and layer limits. Cross-carrier coordination.
Three-party bond structure: principal, obligee, surety. Contract, commercial, and court bonds. Indemnity recovery tracking.
Quota share and excess of loss. Section and layer structure. Participant shares. Cessions and recoveries.
Risk-specific placements. Certificate tracking. Multi-reinsurer participation. Recovery allocation.
Native alignment with PolicyCenter, ClaimCenter, and BillingCenter. Field mappings, typecode translation, and relationship preservation built in.
Mapping layer for Duck Creek policy and claims systems. Same canonical output regardless of source — your analysts don't need to know which system the data came from.
Architecture supports any policy admin, claims, or billing system. Adding a new source means writing one mapping layer — everything downstream stays identical.
665 automated tests across every domain, every LOB, and every edge case we've encountered: mid-term endorsements, retroactive corrections, multi-iteration quotes, cancellation flat, cross-domain claim-to-reinsurance flows.
The hard scenarios aren't afterthoughts — they're in the test suite. Policy corrections that arrive out of order. Claims that span multiple policies. Reserves that go negative then positive. Triangle recalculation on late-reported losses.
Structured onboarding checklist covering discovery, source mapping, crosswalk configuration, test validation, and production cutover. Every deployment follows the same proven sequence.
insurOS isn't just a place to store data. It's a foundation that makes your data usable — with the insurance-specific logic already built in.
Computed at coverage level, by accounting month, automatically adjusted for endorsements, cancellations, and audits. The denominator in every loss ratio — finally accurate without spreadsheet gymnastics.
Slice written premium by producer, program, state, LOB, product, underwriter — any combination. No manual aggregation across systems.
Vehicle counts, property values, payroll, revenue — whatever drives your rates. Tracked through time so you can see how exposure changes, not just current state.
Not just the current reserve — the full progression from FNOL through every reserve change, payment, and recovery. See how the claim developed, not just where it ended up.
Actuarial development triangles built automatically. Paid, incurred, and reported patterns by accident year. Foundation for IBNR estimation and reserve adequacy.
Incurred losses matched to earned premium at the right grain. By program, producer, state, LOB — computed consistently so the numbers actually reconcile.
Track quotes to bind. Hit ratios by producer, product, state. See what you're quoting, what you're binding, and where the leakage happens.
Book size, growth, loss ratio, retention — by producer, agency, or hierarchy level. Identify your best relationships and your problem areas.
For MGAs and program carriers: track performance by program. Premium, loss, commission, and profitability — the metrics that matter for program management.
Loss development triangles by accident year and LOB. Premium by state. Structured for NAIC reporting with package-aware bucketing that matches your rate filings — BOP rolls up correctly, monoline stays separate.
What did we know about this policy on March 1st? Not what it looks like now — what it looked like then. Essential for audits, regulatory inquiries, and reproducing last quarter's numbers exactly.
Ceded premium, recoveries, net retention — by treaty, by layer, by LOB. The data your reinsurance accountants need, without manual extraction from three different systems.
Every data change is versioned. Every pipeline run is logged. Every transformation is documented. When regulators ask how you computed a number, you can show them the exact path from source to output.
Connect Power BI, Tableau, Looker — whatever your teams already use. Star schema designed for analytics. No proprietary interface required.
Your data runs in your own isolated cloud instance. No shared databases. No commingling. Physical separation, not just logical.
Platform access, implementation, operations, monitoring, and updates — all included. No hourly billing. Predictable economics.
Insurance companies — whether admitted carriers, surplus lines writers, or MGAs with delegated authority — that need a unified view of their own data.
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 data →Technology companies building software for insurance — claims automation, underwriting workbenches, submission platforms, agent portals.
The problem: Every InsurTech product needs clean, integrated insurance data. But building the data integration layer isn't your core competency, not what your investors funded, and not what differentiates your product. Yet every deployment triggers the same painful data onboarding.
Economics: Licensed as an OEM component. Bundle it into your subscription pricing.
Explore OEM partnership →Firms that win insurance transformation engagements — from global SIs to mid-market consultancies with insurance practices.
The problem: Every insurance modernization program 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.
Economics: Partner license with per-deployment fee. Embed the cost in your program pricing.
Join the partner program →AI models are only as good as their training data. insurOS delivers unified, historically accurate, cross-domain data — exactly what machine learning models require. Available as expansion tiers for clients ready to move beyond reporting.
Route new claims to the right adjuster. Predict ultimate severity early using historical development patterns and coverage characteristics.
Identify suspicious patterns across the party relationship graph — individuals appearing in different roles across claims, address clustering, provider networks.
Connect submission characteristics to actual loss outcomes. For submissions that looked like this one, what did the claims experience turn out to be?
Feed actuarial models with complete claims development data — reserve changes, payment patterns, recovery trajectories — structured for analysis.
Combine earned premium at coverage level with incurred losses and development factors. 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.