Most AI vendors have never seen a Lloyd's slip. They've never watched a D&O submission sit in a queue for four days while an underwriter chases three PDFs across two inboxes. They've never had to explain an AI decision to a Lloyd's performance review committee. We have. That's not a differentiator — it's the minimum requirement for building AI that actually gets deployed.
Most AI programmes fail because the data underneath them isn't ready. We work the data first, the model second.
In regulated industries, an AI decision you cannot explain is a regulatory finding waiting to happen. XAI sits in the architecture, not on the marketing page.
Human-in-the-loop isn't what you do when the model fails. It's how regulated work is supposed to be done.
A working system in eight weeks beats a flashy demo in three. We architect for the next two years, not the next sprint.
Every person at Marzal Labs has operated inside regulated industries — not just consulted to them. That means we understand the real constraints, the real stakeholders, and the real difference between a demo and a deployed system.
Founder and Principal Architect of Marzal Labs. Over 20 years working inside the UK's most data-complex regulated environments — Lloyd's of London, specialty insurance, NHS, regulated financial services, and government. Led data and AI programmes across Nationwide Building Society, Talbot Underwriting, Gen Re, STARR, and the UK Covid-19 Test & Trace programme. Architecture-first conviction: AI on unprepared data is a liability, not an advantage. MSc, Information Technology.
AI Engineer with a Master's in Applied Linguistics, specialising in LLM workflows, agentic AI orchestration, and NLP pipelines. Applied deep expertise in language structure to develop prompt engineering frameworks, optimise model behaviour, and design natural-language interfaces. Proficient in Python and MCP prototyping, integrating linguistic insight to bridge human communication and AI systems.
Microsoft Fabric, Databricks, and Snowflake specialist with a background in insurance and financial services data architecture. Designed and built the medallion platform that unified 14 source systems for a mid-market enterprise in 16 weeks.
A 30-minute conversation. No deck. Just your situation and an honest read on whether we can help.
help@marzallabs.ai