Insurance software built around your workflow, not a platform vendor's roadmap.

We build across the core insurance software categories: underwriting platforms with risk rules engines and decisioning audit trails, claims management systems from FNOL through settlement, policy administration platforms with product configurators and quote-bind-issue workflows, document intelligence pipelines for policies, claims evidence, and medical reports, and regulatory compliance systems for Solvency II, FCA Consumer Duty, and NAIC. We also build the integration layer between custom-built components and existing core platforms like Guidewire and Duck Creek. The scope depends on what you have, what's breaking, and where the business is losing the most time or money. We assess that in discovery before quoting.

The honest answer depends on your scale, your business rules complexity, and your budget. Guidewire and Duck Creek are mature platforms with deep insurance-specific functionality, pre-built regulatory compliance, and large implementation partner ecosystems. They make sense for mid-to-large insurers with the budget for licensing and implementation (typically $500K to multi-million dollar engagements, and G2's own aggregate review data puts average Guidewire ClaimCenter implementation at 9 months with a 21-month average time-to-ROI). Custom development makes sense when your product structure is genuinely unusual, when your business rules can't be expressed cleanly in a configured platform, when you're a managing general agent or insurtech that needs to move faster than a large platform implementation allows, or when the cost of configuration exceeds the cost of building for your specific scope. We are honest about which fits your situation. We also build the integration layer that connects custom-built components to Guidewire or Duck Creek when a hybrid approach is the right answer.

FNOL automation covers the intake-to-system workflow: extracting structured data from incoming loss notices (phone transcripts, web forms, emails, mobile apps), validating policy coverage against the reported loss date and peril, populating your claims system fields automatically, classifying claim complexity for routing (simple to automated adjudication, complex to experienced adjusters), and generating the acknowledgement communication within minutes of intake. Your adjusters receive a pre-populated claim record rather than a raw loss notice to re-key. We scope the automation boundary clearly during discovery, defining what the system handles and where human judgment takes over, before any development starts.

We build insurance software with compliance requirements built in, not added after the fact. For EU-regulated insurers: Solvency II risk reporting, SCR calculation support, and audit trail requirements for automated decisions. For UK insurers: FCA Consumer Duty documentation, fair value assessment frameworks, and consumer outcome monitoring. For US insurers: NAIC model law requirements vary by state and line of business, but we cover prompt payment compliance tracking, denial letter requirement validation, and documentation requirements for personal and commercial lines. For automated underwriting and claims decisions specifically, we build the audit trail that explains the automated decision in plain language for regulatory examination. We are not a legal compliance firm. For legal sign-off, you need your compliance team and external counsel. We build systems that make compliance operationally achievable.

A focused automation build (FNOL intake, a specific compliance workflow, or a single policy admin module) typically runs $50,000 to $80,000 in 10 to 14 weeks. A full policy administration platform or end-to-end claims management system typically runs $100,000 to $200,000 in 16 to 24 weeks. Document intelligence pipelines for a defined document set typically run $40,000 to $80,000. Cost is driven by the number of systems that need integration, business rules complexity, compliance scope, and whether you need a new user interface or API-only delivery. We give fixed-cost quotes for well-scoped projects after a discovery phase.

AI applies to insurance underwriting in two main ways: risk scoring and document processing. Risk scoring models trained on your historical policy data and loss outcomes generate a structured risk tier and the top contributing risk factors at quote, reducing underwriter time per submission and improving consistency on high-volume personal lines. Document processing extracts relevant data from broker submissions, inspection reports, and prior policy documents automatically, so underwriters work from structured data rather than re-reading raw documents. Both approaches operate as tools that support underwriter judgment, not as black boxes that replace it. The audit trail that explains the AI's scoring contribution is built in from the start. We assess which AI components fit your underwriting workflow and data maturity during discovery.

Data migration from legacy policy systems is one of the riskier parts of any insurance software replacement, and we treat it as a first-class workstream rather than an afterthought. The migration approach: data profiling to understand the actual shape of your legacy data (which fields are populated consistently, which are sparse, which have changed meaning over time), mapping from legacy schema to new schema with explicit decisions on how to handle gaps and inconsistencies, a test migration on a representative subset before the full migration to validate output quality, and parallel running where both systems are live for a period so your team can validate the migrated data against the source. Policy-level reconciliation reports confirm that premium, coverage, and term data matches before legacy decommissioning. For active claims in progress during migration, we design the cutover timing and data state to avoid losing claim history or adjuster notes.

We work in insurance the same way we work in every regulated domain we build for: the engineers who scope your workflow learn your actual claims process, your actual policy structure, your actual compliance obligations, in discovery, before writing a line of code, rather than arriving with a generic template. We're direct about where that domain knowledge is deep versus where it's newly built for your specific engagement. What's constant across every insurance project is the same rigor: named FNOL and MTA workflows handled correctly, a real Guidewire and Duck Creek integration layer, and compliance frameworks scoped by requirement, not by buzzword.