Your claims data lives in twelve systems. Your actuaries reconcile it by hand.

Insurance companies and InsurTech platforms manage some of the most complex data structures in any industry. Policy hierarchies, claims workflows, provider networks, reinsurance relationships, and regulatory reporting requirements create a data environment where getting a single accurate number is genuinely difficult.

Most insurance organizations we talk to share the same set of problems: data spread across legacy systems that were built or acquired at different times, reporting that takes days instead of minutes, platform costs that grow faster than the insights they deliver, and no internal data team with the capacity to fix the underlying infrastructure. The business runs on data, but the data infrastructure was never designed for how the business actually operates today.

Claims and policy data unification. Policy administration, claims management, billing, and underwriting systems each hold a piece of the truth. We build pipelines that extract from all of them, normalize the data into governed models, and make it available for reporting and analytics. The result is a single source of trust for loss ratios, claim velocity, policy profitability, and the other numbers your actuaries and underwriters need without manual reconciliation.

Reporting automation that meets compliance deadlines. State filings, NAIC data calls, and compliance deliverables are deadline-driven, multi-source, and currently manual at most organizations. We standardize disparate reporting logic into governed models and automate the processes that currently consume days of analyst time. At Blitz Medical Billing, month-end reporting went from 8 hours per customer to 30 minutes for all customers combined. Insurance regulatory reporting follows the same pattern and responds to the same fix.

Cost-effective data infrastructure. Insurance companies do not need to spend six figures on warehouse credits to run the queries they actually run. We profile real usage patterns — query volumes, data sizes, concurrency needs — and migrate to platforms that match. We have reduced ELT costs by up to 80% and compute costs by 30% or more across clients. We evaluate whether migration makes sense before recommending it.

Embedded analytics for insurance products. InsurTech platforms that need to surface data to policyholders, agents, or partners need an analytics layer that integrates directly into the product. We build embedded dashboards and reporting interfaces from assessment to production, with the access controls and data governance that regulated environments require.

We understand claims data hierarchies, regulatory deadlines, multi-stakeholder reporting demands, and the reality that most insurance organizations cannot hire a full data team on the timeline they need one. Our assessment-first model means you see working results before committing to a full build — typically from assessment to production proof of concept in 45 days.