

Insurance Software Development
Policy administration, claims systems and process automation for insurers, MGAs and brokers, built to work with the core platforms you already run rather than around them.
TRUSTED BY TEAMS
Sodio builds insurance software development covering policy administration, claims management, health insurance platforms and policyholder apps, alongside insurance process automation and RPA across legacy systems.
We also build insurance AI for claims processing, fraud detection, document handling and churn prediction. Insurance runs on systems that were bought a decade ago and cannot be replaced, so most of the useful work is integration and automation around them rather than replacement of them.
/// WHAT MAKES INSURANCE DIFFERENT
The Cost Is in the Handoffs
The Document Business
Insurance is a document business running on systems bought a long time ago. Most of the operational cost is not in any single step — it is in the gaps between them.
Handoff Cost
A claim arrives as a phone call, an email, a photograph and a PDF. Someone reads it, keys it into one system, looks up the policy in another, requests a document, waits, chases, then rekeys the outcome somewhere else. Each handoff adds days and an opportunity for error, and none of it is visible as a line item. It shows up instead as cost per claim and as cycle time.
Automation Over Replacement
That is why automation is where the return is, and why replacement usually is not. Core policy and claims platforms represent years of configuration and regulatory approval. Replacing one is a multi-year programme with a poor success record. Automating the work around it delivers measurable results in months, and the two are not the same proposition.
RPA as an Honest Answer
Where no API exists — and in insurance that is common — RPA against the user interface is sometimes the honest answer rather than a rewrite. It is not elegant. It works, and it does not require the vendor's cooperation.
Explainability Constraint
The constraint on all of it is explainability. An underwriting decline or a claims decision has to be reconstructable, with the factors that drove it. That shapes how AI can be used here: to surface, extract and recommend, with a human accountable for the outcome.
/// INSURANCE SOLUTIONS
Insurance Software We Build
Insurance Software Development
Insurance Mobile App Development
Custom Insurance Software
Policy Administration Systems
Claims Management Systems
Insurance Process Automation
RPA for Insurance
Cloud Insurance Software
Insurance Technology Consulting
Health Insurance Platforms

///AI FOR INSURANCE
AI for Insurance
Insurance AI earns its place where it removes a handoff or catches something before payout. Every model here attaches to a number an insurer already reports: cost per claim, cycle time, fraud loss, combined ratio, renewal rate.
AI Claims Processing
FNOL intake, document extraction, triage and settlement recommendation. The largest operational cost line in any insurer.
Insurance Fraud Detection
Claims fraud scoring at submission rather than after payout, tuned against your own confirmed fraud history.
AI Underwriting
Risk assessment with feature-level attribution and a decision audit trail, for both insurance and lending underwriting.
Document Processing AI
Policies, claims forms, medical reports and loss adjuster notes turned into structured data with review workflow.
Chatbots for Insurance
Policy questions, claim status and first notice of loss, grounded in real policy data with scoped permissions.
Customer Churn & Retention AI
Renewal prediction with the reason and the intervention, weeks before the renewal notice goes out.
Pricing & Risk Modelling
Actuarial support rather than replacement — models that surface signal your pricing team validates and owns.
Blockchain in Insurance
Parametric cover with smart contract settlement, shared claims registries and reinsurance treaty automation.
FNOL intake, document extraction, triage and settlement recommendation. The largest operational cost line in any insurer.
Learn MoreClaims fraud scoring at submission rather than after payout, tuned against your own confirmed fraud history.
Learn MoreRisk assessment with feature-level attribution and a decision audit trail, for both insurance and lending underwriting.
Learn MorePolicies, claims forms, medical reports and loss adjuster notes turned into structured data with review workflow.
Learn MorePolicy questions, claim status and first notice of loss, grounded in real policy data with scoped permissions.
Learn MoreRenewal prediction with the reason and the intervention, weeks before the renewal notice goes out.
Learn MoreActuarial support rather than replacement — models that surface signal your pricing team validates and owns.
Learn MoreParametric cover with smart contract settlement, shared claims registries and reinsurance treaty automation.
Learn More
///RELATED SECTORS
Related Sectors
Fintech, banking, lending, payments and RegTech
Learn MoreClinical systems, EHR integration and medical software
Learn MoreSmart contracts, tokenisation and Web3 infrastructure
Learn More///SYSTEMS AND INTEGRATIONS
Systems We Integrate With
/// HOW WE WORK
How We Work on Insurance Projects
Process and systems audit
We follow a claim or a policy end to end, counting the handoffs and the rekeying. Then we establish what each system genuinely exposes — API, event stream, database, file exchange or nothing at all.
Free solution architecture
Automation candidates ranked by return, integration approach per system, AI feasibility and a costed delivery plan. Yours to keep whether or not you build with us.
Pilot on one process
One workflow, running against real data with real users. Handling time and error rate are measured before and after, so the result is a number rather than an impression.
Production rollout
Extended process by process, with monitoring, exception handling and escalation paths. We do not attempt an estate-wide automation programme in a single release.
///FEATURED CASES
Future-Proof Software for Your Business
At Sodio, we deliver mobile apps, web apps, blockchain (DApps), AI integrations, SaaS platforms, and custom software development. Our innovative solutions are scalable, secure, and user-friendly, designed to drive growth and efficiency, keeping your business ahead in the competitive landscape. Trust Sodio for your digital transformation needs.
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/// FAQ
Frequently Asked Questions
Usually, though the method varies. Modern platforms such as Guidewire, Duck Creek and EIS expose APIs and event streams. Older on-premise systems often mean an integration layer, database-level extraction or scheduled file exchange instead. Where a system has no usable interface at all, RPA against the user interface is sometimes the honest answer rather than a rewrite. We establish what genuinely exists during discovery.
It removes handoffs rather than people. The work that automates well is high-volume, rules-driven and document-heavy: data re-entry between systems, claims document classification, renewal processing, reconciliation and compliance reporting. Underwriting judgement and complex claims decisions stay with humans. Anyone promising to automate those is either overselling or has not read the regulatory requirements.
It can support them. In regulated markets the requirement is explainability — which factors drove the outcome, what the applicant can be told, and a decision trail a regulator can reconstruct. We build models with feature-level attribution and keep a human accountable for declines and referrals. An opaque model making binding underwriting decisions is a compliance problem waiting to surface.
With the same discipline any regulated data demands: access controls, audit logging, encryption in transit and at rest, and developers working against anonymised or synthetic datasets wherever the work allows it. Where medical data is involved, health data rules apply on top.
All three, though the problems differ. Insurers need core system work and integration at scale. MGAs need speed to market on new products and the rating flexibility to support them. Brokers need distribution, quoting across carriers and client management. The engineering discipline is shared; the constraints and timelines are not.
For a defined scope we target a working MVP in 30 days and a core production build in 90. Insurance extends that more often than most sectors: core system integration approval, regulatory review, actuarial sign-off and phased migration all sit outside our control. We flag which apply during the free solution architecture.
/// RELATED SERVICES
Related Services
Internal linking back into the main service tree.
/// GET STARTED
Start With One Process
Tell us which process costs the most to run and which systems it touches. We will prepare a free solution architecture ranking the automation candidates by return, with an integration approach for each system, so you can judge the case before committing.