Whether you need to automate a single process or rebuild your entire data infrastructure, we scope it, price it, and deliver it. End to end.
Get in touch
AI and data engineering for reinsurers.
We build the data foundations that make AI work - and the tools that sit on top.
Advise. Design. Build.
This isn't a sequential process - it's how we operate. Every engagement draws on all three, whether it takes three weeks or three years. The balance shifts depending on where you are.
Advise
We learn your business, identify where AI solves real problems, and scope what needs to happen. Workshops, deep analysis, AI strategy - from people who already understand reinsurance. Sometimes this is a two-week diagnostic. Sometimes it's embedded alongside your team for months. Either way, we're not starting from scratch.
Design
We turn understanding into architecture, plans, and prototypes you can evaluate before we build. Data models, system design, integration maps - everything scoped and priced so you know exactly what you're getting. You evaluate it before we build it.
Build
Bespoke code, delivered end to end. Scoped and priced before we start. Because we keep the context from advisory and design through into the build, you don't lose months to handovers or re-learning. And once the foundation is in place, every subsequent project builds on what's already there. We use AI across our own engineering process too - it's one of the reasons we move fast.
What changes when the data foundation is right.
Clean data layer: every team draws from the same structured, validated data. Changes propagate once. No more reconciliation across spreadsheets.
Automated pipelines: ingestion, validation, and transformation handled automatically. Your people spend time on analysis, not data prep.
Infrastructure that supports AI: models work because the data underneath is clean, consistent, and accessible. Not bolted on after the fact.
Each project builds on the last: the data layer and pipelines are already there. Second project is faster than the first. Third is faster again.
Less reliance on key people: critical processes codified, not dependent on any one person. The system handles new treaty types without rework.
Common challenges we solve
How do I get AI working when our data isn't ready?
Three things need to be true before AI can run reliably. The data needs to be clean and well-structured. Someone needs to understand - deeply - what your people do day to day. And your team needs to trust the systems enough to actually use them. We build the first.
We work alongside your team to figure out the second. And we stay close enough to make the transition stick.
How do I automate without losing control?
Three teams, three versions of the same settlement data. Because there's no single source of truth to work from. So everyone reconciles everything, every time.
We codify the repetitive processes so your specialists can focus on analysis, not admin.
How do I scale without scaling the team?
Every new book means more treaty obligations to track, more data to reconcile, more coordination across teams. Right now, most of that knowledge lives in people's heads or buried in documents that nobody can search.
Once your data foundations are solid and your core processes are codified, onboarding new books doesn't require new headcount. The infrastructure handles it.
Tools built on real reinsurance data.
Tools we've built for reinsurers - using live data, inside working firms.
You don't have to wait until everything's perfect to start seeing value.
Ask your data a question. Get an answer.
Natural language querying
Query structured data in plain English. Charts, tables, analysis back. No SQL.
Portfolio dashboards
KRD dashboards, investment performance, portfolio monitoring - updated live.
Data discovery
Surface patterns, gaps, and connections across your data estate.
Catch bad data before it gets in.
File pattern analysis
Compares incoming files against expected patterns. Deviations flagged before processing.
Vendor data mapping
Parses third-party file structures, maps columns, flags format changes.
Quality scoring
Every incoming file scored on completeness, consistency, and timeliness.
Make your documents searchable.
Contract clause inspection
Extracts reserving rules, schedules, obligations from treaty documents.
Enterprise knowledge search
Semantic search across internal docs. Plain English questions, sourced answers.
Regulatory analysis
Structured summaries of regulatory guidance. Tested on BMA and BSCR docs.
Do more with less.
Workflow automation
Automate steps between systems. Team focuses on judgement, not admin.
Pipeline debugging
Diagnose and fix data pipeline issues in plain language.
Know when assumptions stop matching reality.
Anomaly detection
Flags unexpected shifts in data patterns.
Automated alerting
Right people told about right problems before they compound.
Start with one problem. Then keep going.
Most clients start with a single project - a settlement process that's too slow, a data feed that's unreliable, a reporting cycle that eats a whole team's week. We fix it.
And once the data foundation is in place for one area, extending it across the business gets faster and cheaper each time. The data layer, the pipelines, the governance - each one makes the next project faster.
Learn more about us