Insurance software that handles complex policy logic, claims workflows, and compliance — without the mainframe.
Madgeek builds insurance software — claims management platforms, policy administration systems, agency management tools, and AI-powered underwriting automation — for insurance carriers, MGAs, and insurtech companies in the US, UK, and Canada. Compliance-first architecture. AI included on every engagement. Senior engineering team in India. 50+ enterprise systems shipped since 2017.
Building enterprise software since 2017
Enterprise systems shipped across regulated industries
Production AI systems deployed in operations
Clutch rating from verified reviews
Most insurance software projects die in the integration phase.
Insurance operates on legacy core systems — mainframes, COBOL-era policy admin platforms, AS/400 databases — that vendors built integration-proof by accident. Every API call to a modern claims platform has to translate data from a 1980s data model. Off-the-shelf insurtech tools assume you're on a modern stack. You're not.
State-by-state compliance is not optional. Rate filings, form approvals, surplus lines regulations, NAIC reporting — every jurisdiction has different requirements, different timelines, different data formats. Platforms built for one market require expensive customisation to operate across multiple states. The regulatory gap shows up in production, not in the demo.
The claims workflow is where generic platforms break. Subrogation logic, reserve calculations, co-insurance and reinsurance allocation, salvage recovery — these are not standard features in an off-the-shelf claims system. Your ops team builds spreadsheets alongside the platform. The spreadsheets become the system of record.
The cost is the claim leakage. Manual touchpoints in claims processing add days per claim. At scale, every day adds up to millions in extended reserves and administrative overhead. The platform isn't slowing you down — the workarounds around the platform are.
Building insurance software that needs to handle real policy complexity? Let's talk about what a purpose-built system looks like.
Book a 30-minute callInsurance software built around your policy model — not a generic insurance template.
We start with your actual policy model — the coverage types, the pricing logic, the endorsement rules, the state-specific compliance requirements. Then we build an architecture that enforces your rules at the data layer, not in application code that gets bypassed.
AI is included on every engagement. Automated claims triage, document classification for FNOL intake, underwriting risk scoring, fraud pattern detection, reserve adequacy modeling — if an AI capability reduces loss ratios or claims handling time, we build it in. Every AI feature in an insurance context includes explainability and audit trails required for regulatory review.
Senior engineers in Bengaluru, India with a US office in Irvine, California. The team that designs the claims workflow architecture is the team that ships it and maintains it. We've built for regulated enterprise environments for 8+ years — including publicly listed companies with strict audit requirements.
What we build for insurance.
We build for regulated, complex environments. Insurance is the same engineering challenge.
Compliance-grade security, audit trails, complex business rules, multi-role access control, integration with legacy systems — these are the engineering problems we've solved across regulated industries for 8+ years.
Tejas Networks: enterprise platform in a regulated environment
Situation: A publicly listed telecom equipment manufacturer ran multi-level purchase requisition approvals on paper forms. Physical sign-off at each tier. Finance and operations had no visibility into pending, approved, or blocked requests. Strict compliance requirements for audit trails and access control.
What we built: We built a purchase requisition platform with role-based approval chains, configurable escalation rules, real-time dashboards, and full audit trail on every transaction. Compliance-grade access control with department-level permissions and multi-tier approval workflows.
90% reduction in paper-based approvals
AI in production operations: 50 to 80+ agents in 3 months
Situation: A growing operations team needed to scale quality assurance from 50 to 80+ agents without adding management headcount. Manual monitoring couldn't keep pace with growth, and quality consistency was slipping.
What we built: Custom AI-powered call quality monitoring with automated scoring, performance dashboards, and coaching workflows. The AI system processes every interaction, flags quality issues, and surfaces patterns — replacing manual review that would have required dedicated QA staff.
50 → 80+ agents scaled in 3 months
Manufacturing ERP: complex business rules with audit trails
Situation: A manufacturer needed a custom ERP to handle non-standard cost estimation, procurement workflows, and production scheduling. Off-the-shelf ERP systems couldn't model their pricing rules or approval hierarchies.
What we built: Purpose-built ERP with configurable business rules, multi-level approval chains, real-time cost tracking, and full audit logging. Every calculation traceable. Every approval recorded. Integration with existing accounting and inventory systems.
Complex business rules + full audit trails
What we build for insurance companies and MGAs.
Every insurance engagement is different. Here's the range of what we build — configured to your coverage model, compliance requirements, and distribution architecture.
End-to-end claims handling from FNOL through settlement. Configurable workflow rules, reserve management, subrogation tracking, and reinsurance allocation. Built for your coverage types, not a generic property or casualty template.
New business, renewal, endorsement, and cancellation workflows with state-specific rating engines, form libraries, and surplus lines compliance. Integrates with your existing core or replaces it entirely.
Producer-facing portals for quoting, binding, and commission management. White-label capable. Built to match your distribution model and product mix.
Risk scoring models trained on your book of business, automated document classification, fraud detection, and reserve adequacy analytics. Built for production, not proof of concept.
Three concerns insurance companies raise.
"Our core system is a mainframe — can you integrate with it?"
Yes. We've built integration layers for legacy policy admin platforms, COBOL-era core systems, and AS/400 databases. The integration layer handles data translation, field mapping, and error recovery between your legacy core and modern applications. We don't require you to replace the core to build modern tooling around it.
"Insurance software needs to be compliant across multiple states. Can you handle that?"
State-by-state compliance is built into the architecture, not applied as a configuration layer. Rate filing logic, form approval tracking, surplus lines reporting, and NAIC data format requirements are addressed at the data model and workflow layer. We've built compliance-grade enterprise systems for publicly listed companies with multi-jurisdiction requirements.
"How do you handle PHI and sensitive policyholder data?"
Policyholder data is subject to state privacy laws, GLBA at the federal level, and where health data is involved, HIPAA. Our architecture applies encryption at rest and in transit, role-based access control with audit trails, access logging, and data segregation from the ground up. Production environments never mix with development environments. We can deploy on your existing compliant infrastructure or recommend a compliant cloud setup.
How insurance engagements work.
Every engagement follows the same structure — with compliance built into every stage, not added at the end.
Enterprise systems we've shipped.
Production platforms for regulated industries, complex workflows, and enterprise operations — built and maintained long-term.
AI Call Center Software for Quality Monitoring
Enterprise client
A contact centre operation was scaling rapidly but had no automated way to monitor agent call quality at volume. Madgeek built custom AI call center software that scored agent calls against domain-specific criteria, surfaced coaching opportunities, and tracked performance trends in real time. The result: the operations team scaled from 50 to 80+ agents in 3 months without adding QA headcount.
agents scaled in 3 months
Custom Purchase Requisition Software for Enterprise
Tejas Networks Ltd.
A publicly listed telecommunications manufacturer was running procurement entirely on paper forms and manual approval chains. Madgeek built custom purchase requisition software with automated approval routing, purchase order generation, real-time inventory tracking, and document management. The result was a 90% reduction in paper-based approvals and full visibility across the procurement lifecycle.
reduction in paper-based approvals
Custom eCommerce Platform — Retail Rebuild
CrazyPi (Remote Computing Technologies)
A market-leading electronics retailer had outgrown its existing platform — slow page loads, high checkout abandonment, and a promotional engine that could not handle complex discount structures. Madgeek built a custom eCommerce platform from the ground up: performance-first architecture with sub-2-second page loads, mobile-native checkout, and an advanced promotional engine for tiered pricing, bundle deals, and flash sales. The result was a 40%+ increase in sales within the first quarter.
increase in sales after platform rebuild
Common questions about insurance software development.
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Start with a scoped proposal — not a sales deck.
We review your compliance requirements and system landscape before we write a line of code. Discovery calls are 30 minutes. Proposals arrive within 5 business days.
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