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Team Since 2018
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Projects completed
Headcount growth 2025
We’re innovators, making AI work for everyone. With trusted partners like AWS and NVIDIA, we turn ideas into real-world solutions.
What truly defines us is our people. We’re an inclusive, forward-looking team that supports each other, learns together and shares a passion for building what’s next.
Open positions
Why join us?
We’re a team of curious minds building AI that changes how people work and live, and we want you with us.
Building things that matter
Shaping work lives with meaningful, innovative solutions
Work Flexible and Empowered
Low hierarchy, hybrid work, your voice heard
Grow with us
Your career, boosted by AWS and NVIDIA
Four values shape how we work together, serve our customers and push new ideas forward.
Challenge Accepted
Proactive - Helpful - Get it done
Do what it takes
No excuses - Tenacious - Relentless
Consistently Deliver
Self-motivated - Dedicated to the cause - Disciplined and focused
Aim Higher
Be your best - Think big - Dare to lead
Open Application
Tech Champion
Client Champion
Operations Champion
What’s New at Firemind
Catch up on our latest thinking, conversations, and customer success stories.
MoneySuperMarket Boosts Insurance Conversions with AI Agents: 30% Faster Insights & 90% Data Accuracy
MoneySuperMarket (MSM), the UK’s leading price comparison platform for financial services, partnered with Firemind to transform its customer experience using AI-driven insurance insights.
✔︎ AI‑driven document summarisation
✔︎ Secure, scalable AWS-based solution
How to identify the most common mistakes in GenAI data preparation?
Identifying common mistakes in GenAI data preparation is crucial for AI success. The primary errors—insufficient data cleaning, poor structure, inadequate labeling, and misaligned formats—can reduce model accuracy by up to 40% and significantly increase processing time. Rather than costly system rebuilds, managed AI solutions offer a practical alternative. These intelligent systems integrate with existing workflows to automatically identify and fix data quality issues through automated checks, intelligent mapping, and adaptive cleaning processes. By addressing these preparation mistakes incrementally, organisations can improve their AI outcomes within weeks whilst maintaining operational continuity and avoiding the risks of complete system overhauls.
From Chaos to Control: AI Incident Management as a Managed Service
From manual ticket triage to AI-powered incident management
