About
An AI lab with products and platforms.
PixelForge AI Labs Ltd is an independent AI lab based in London, England. PixelForge Labs builds long-term B2B partnerships. PixelForge Apps turns new AI capabilities into consumer products people can put to use today.
Our mission
AI should behave like infrastructure: dependable, observable, and composable. Too often it is an experiment left running in production. Our mission is to turn modern AI capabilities into systems that teams can build on for years.
From first prototype to scaled deployment, PixelForge Labs helps product and engineering leaders design architectures that are ambitious in scope and disciplined in operation.
How we work
We combine research sensibilities with pragmatic engineering. That means rigorous evaluation, careful data and prompt design, and an uncompromising view on safety, monitoring, and human-in-the-loop controls.
Our work spans autonomous agents, AI-powered automations, fine-tuned models, and focused utility applications. PixelForge Apps packages the same capabilities into subscription products on the web, the App Store, and the Play Store.
Trajectory
From experiments to enduring systems.
Four phases that take an idea from a careful discovery to a system that keeps compounding value.
-
01 · Discovery
Map constraints and opportunities
We start with your workflows, risk surface, and data reality, not with a model name. Together we define where AI can be safely inserted and what success should look like.
-
02 · Prototyping
Design and test candidate systems
We prototype agents, automations, or model variants quickly, then put them through adversarial evaluation so we understand their behaviour before they go anywhere near production.
-
03 · Hardening
Instrument, monitor, and harden
We surround systems with observability, feedback loops, and guardrails so that issues surface early and can be corrected with intention, not urgency.
-
04 · Evolution
Keep improving as you grow
As your data and products evolve, we help you retrain, retune, and extend systems so they continue to deliver compounding value.
Team
Built by AI practitioners.
Founder & CEO
Vision for production AI systems
Former ML engineer with experience scaling AI infrastructure at enterprise companies.
Head of Engineering
Reliable, observable AI systems
10+ years building distributed systems, now focused on AI safety and reliability.
Head of Research
Fine-tuning and evaluation methods
PhD in Machine Learning, published researcher in LLM alignment and evaluation.
Let’s build something dependable.
Tell us about your workflows, your stack, and your constraints. We will respond with a clear, pragmatic view on where AI can be safely inserted.