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Industries
Insurance & Warranty
Underwriting and claims, engineered for the next decade.
Re-platforming policy admin, underwriting, and claims into cloud-native, AI-augmented systems — without disrupting the operating spine the business runs on.
The case
Carriers don't fail at strategy.
They fail at execution velocity.
Most insurers have a multi-year transformation deck. What stalls is the seam between thirty-year-old core systems and the modern data, AI, and digital experience the strategy depends on. The mainframe doesn't go away — it gets wrapped, instrumented, and progressively offloaded to a cloud-native intelligence layer.
We engineer the layer that sits between legacy core and modern customer experience: a unified data spine, AI-augmented underwriting and claims, and a federated DevSecOps model that lets dozens of squads ship safely against regulated, audited workloads.
How we engineer for Insurance
The capabilities
that compound here.
Data Lakehouse & Warehouse
Unify policy, claims, and third-party data into one governed estate — the foundation for every AI workload downstream.
Enterprise AI
An AI control plane for underwriting, claims triage, and fraud — model registry, governance, FinOps, and shared infrastructure.
Cloud DevSecOps
Federated DevSecOps with policy-as-code, compliance evidence baked into pipelines, and zero-trust by default.
Custom Software Development
Modern policy admin layers, broker portals, and claims experiences — wrapped around legacy core, not betting against it.
Outcomes we engineer for
Numbers that move
at the operating level.
−68%
Quote-to-bind time
+4.2pp
Loss-ratio lift from AI underwriting
−31%
Cloud spend (FinOps)
100%
Audit readiness, continuously
Common questions
What buyers
ask first.
Can you work alongside our existing core systems vendor?
Yes — most engagements explicitly preserve and extend the core. We engineer the data spine, AI layer, and digital experience around it, with clear contracts back to the core.
How do you handle regulated data and audit?
Policy-as-code, evidence-baked pipelines, immutable lineage, and continuous control attestation. Auditors get queryable evidence; regulators get a live posture, not a quarterly snapshot.
How fast can a first AI workload go live?
Triage and decisioning copilots typically reach pilot in 6–10 weeks on top of an existing data foundation. The control plane and governance precede the model — never after.
Related industries
Where the same
playbook applies.
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Let's compare notes
Engineered for the carriers
that compound, not catch up.
Tell us where the underwriting–claims–data seam breaks down. We'll diagnose, frame, and propose a starting point that pays back inside a quarter.