Do you work with insurers or InsurTech vendors?

My experience has been on the vendor side, building claims technology that integrates with insurer systems. That perspective is useful for investors and insurers evaluating vendor platforms, and for vendors who need someone who understands the real integration challenges beyond the sales demo.

What makes your approach different from insurance-native consultants?

I bring 20 years of cross-industry engineering experience into insurance. I've built mission-critical systems for emergency services, real-time platforms for live events, and multi-tenant SaaS at scale. Insurance is one of several regulated, high-stakes environments I've worked in. That outside perspective is often more valuable than deep industry tenure, particularly when the industry's established approaches aren't delivering.

What is your experience with AI in insurance claims?

I led the technical architecture, deployment strategy, and compliance planning for an LLM integration project in claims processing, part of an Innovate UK-funded initiative. My role covered everything from infrastructure and resilience through to regulatory readiness. I understand the production readiness challenges that most AI demos don't address.

Service

Claims & InsurTech Advisory

Q: What areas of insurance technology do you cover?

My experience is in P&C claims technology, specifically motor and home. I've worked on digital FNOL platforms, self-service claims journeys, and the integration challenges that come with connecting claimants, insurers, and supplier networks. I also have hands-on experience managing AI and LLM integration projects in regulated claims environments.

Cross-industry thinking applied to claims technology.

I'm not an insurance lifer. I'm a technologist who's spent several years building and fixing claims platforms in P&C motor and home, after two decades building mission-critical systems in other regulated industries.

That outside perspective is often exactly what's needed. Insurance technology has a tendency to reinvent problems that other sectors solved years ago. I bring patterns from emergency services, real-time event systems, and multi-tenant SaaS into an industry that doesn't always look beyond its own walls.

What I know, and what I don't

I know: Digital FNOL, self-service claims journeys, supplier network integration, P&C motor and home claims workflows, AI governance for regulated claims environments, and what it takes to get a claims platform from demo to production.

Not my core expertise: Guidewire internals, commercial specialty lines, reinsurance, legacy policy administration systems, or the deep actuarial side. I'm not going to pretend otherwise. But if you've got a technical problem in those areas, I'm happy to take a look and help where I can. A fresh pair of eyes often finds things domain expertise misses.

When this is useful

You're building or fixing a digital claims platform and need someone who's been through it
You're evaluating AI or LLM integration for claims and want a realistic view of what production actually requires
You're an investor looking at an InsurTech acquisition and need technical assessment with some claims context
Your claims transformation is stuck and you suspect the problems are as much technical as they are organisational
You want a perspective from outside the insurance echo chamber

What I actually bring to this

Cross-Industry Pattern Recognition

I've built systems for fire and rescue where response times are measured in seconds and failure means something. I've built real-time tracking platforms where data has to be right the first time. Those environments taught me things about resilience, integration, and operational readiness that translate directly to claims technology. Insurance isn't unique in needing systems that work under pressure. It just thinks it is.

FNOL and Digital Claims Experience

I've worked hands-on with digital FNOL platforms for motor and home. Not greenfield builds with unlimited budgets, but fixing and extending platforms that someone else built, integrating with supplier networks, and dealing with the real operational complexity that clean demos don't show. If your platform has rough edges, I've probably seen similar ones.

AI Governance in Practice

I led the technical architecture, deployment, and compliance planning for an LLM integration project in claims processing as part of an Innovate UK-funded initiative. Everything from infrastructure and resilience through to regulatory readiness. The project taught me exactly where the gap sits between an impressive demo and a production-ready system in a regulated environment. That governance gap is where most claims AI initiatives stall.

Technical Depth Without Industry Blinkers

I can talk to your developers about API design and your board about platform risk in the same day. But I'm not going to pretend I know your industry better than you do. What I will do is challenge assumptions that go unquestioned because "that's how insurance works" when other sectors found better answers years ago.

How this typically works

Advisory and Sounding Board

Ongoing access for claims technology leaders who want an outside perspective. Architecture decisions, vendor evaluations, "is this normal or are we doing something wrong?" conversations. Flexible cadence based on what you need.

InsurTech Technical Assessment

For investors or insurers evaluating claims technology vendors. I combine standard technical due diligence with enough claims domain context to assess whether the platform will actually work in a real operational environment, not just in the sales demo.

AI Readiness Review

Practical assessment of your AI or LLM integration plans for claims. Not a theoretical governance framework, but a realistic look at what needs to be true before you go live in a regulated environment. Where are the gaps? What will your compliance team flag? What does production actually require?

Platform Review

Assessment of your digital claims platform with a focus on FNOL, self-service journeys, and supplier integration. I'll identify the architectural risks, the integration pain points, and the places where cross-industry patterns could improve what you've got.

Writing on claims technology and AI

I write about what I've seen in practice, including the things that didn't work. These are practitioner observations, not industry analysis from the sidelines.

Agentic AI in Insurance Claims →The Claims Spectrum: Why Not All Claims Are Equal →LLMs in Production: The Governance Gap →

Common questions

What areas of insurance technology do you cover?

P&C claims technology, specifically motor and home. Digital FNOL platforms, self-service claims journeys, supplier network integration, and AI governance for regulated claims environments. I'm not an expert in commercial specialty lines, reinsurance, or legacy policy admin systems, but if you've got a problem in those areas I'm happy to look at it and help where I can.

Have you worked at an insurer?

No. My experience is on the vendor side, building claims technology that integrates with insurer systems. I understand the integration challenges, the data flows, and the operational requirements from the technology perspective. If you need someone with underwriting or actuarial background, that's not me.

What makes your approach different from insurance consultancies?

I bring 20 years of cross-industry engineering into insurance. I've seen how emergency services handle real-time coordination, how event platforms manage data at scale, and how multi-tenant SaaS solves problems that insurance vendors are still struggling with. The value isn't that I know insurance better than you. It's that I know what other industries have already figured out.

What was your role in the AI claims project?

I led the technical architecture, deployment strategy, resilience, and scalability planning for an LLM integration project in claims processing, part of an Innovate UK-funded initiative. Everything except writing the prompts, basically: how to get the infrastructure right, how to make it resilient, how to satisfy compliance, and how to get from a promising proof of concept to something that could actually run in production under regulatory scrutiny.

Related services

Technical Due Diligence →Platform Health Check →Architecture Review →

Working on claims technology?

Whether you need a sounding board, a reality check on your AI plans, or someone who'll challenge the way things have always been done, let's talk.

Book a 30-Minute Call Email Instead

References available on request. I typically respond to emails within 2 business days.