// AI FOR
Enterprise AI Consultancy & Agentic AI Engineering — London
We help enterprises pick the few
AI bets that matter — and get them
into production, not stuck in pilots.
Applied AI Engineering · London · Est. 2022 · Founded by the former European CTO of IBM Watson
OUR
WORK
[ CLICK LOGO FOR CASE_STUDY ]
// TESTIMONIAL
PARTNERSHIP
3+ years
Dr Oliver Bogler
Director, NCI's Center for Cancer Training
“I have worked with Barnacle Labs for more than 3 years on a project at the National Cancer Institute (NCI)... they treated the work like a collaboration... if you are looking for a partner in AI, I couldn't recommend them more.”
WHO
WE ARE
// BACKGROUND
Our founders have been building with modern AI for over a decade — from leading AI at IBM Watson to securing early GPT-3 access in 2020.
// THE MISSION
We build production AI systems for high-stakes environments—including the US Federal Government, financial services, global enterprises, and biotech firms. We specialise in the hard parts that quietly derail AI projects, bringing creative problem-solving rooted in experience, not guesswork.
// ENTERPRISE_AI
HOW
WE HELP ENTERPRISES PUT AI TO WORK
// OUR_APPROACH
01
Find the opportunity
Pick the AI bets that matter.
02
Build the system
Ship production systems, not demos.
03
Make it stick
Equip your team to own and evolve what we build.
// OUR_SPECIALISMS
Where Barnacle goes deep
We start with your workflows, constraints and priorities, then shape the right solution for your environment.
01Autonomous agents
02Agent memory systems & context graphs
03Sovereign AI deployments
Using our proprietary research assets Minerva and Alexandria to move from prototype to production faster.
[ EXPLORE_OUR_SERVICES → ]// DEFINE THE PROBLEM BEFORE YOU COMMIT THE CODE
Executive AI Workshop
01Shared view of AI across your leadership team
02A shortlist of AI initiatives ranked by what's real, not what's shiny
03Clear criteria for where to start
Live demos, real conversation, and a roadmap you can act on.
[ LEARN_MORE → ]// GET_STARTED
Not sure where to start?
Talk to an engineer about your workflows, constraints, and opportunities — and we'll show you where we'd focus first.
// WHY_BARNACLE
Working code. Not slide decks.
We don't do six-month discovery phases that end in a 100-page PDF. We put working software in your hands in weeks, not months. If an AI bet isn't going to work, we want you to know on Day 15, not at the end of Q3. We get you out of pilot purgatory and into production.
READ
OUR THOUGHTS
Thought leadership & research
GUIDE
AI Agents for Enterprise
A strategic guide for enterprise leaders on building AI agents at scale. Covers architecture patterns, deployment strategies, and the governance frameworks that separate successful agent programmes from expensive experiments.
[ READ → ]
GUIDE
Agent Memory Systems
Giving agents real memory — beyond context windows and vector databases. How to build systems that remember what matters, forget what doesn't, and get smarter with every interaction.
[ READ → ]
GUIDE
The OpenClaw Ecosystem
Inside the fastest-growing open-source agent framework and what it means for enterprise. A deep dive into the ecosystem and why enterprises are starting to take notice.
[ READ → ]
GUIDE
Sovereign AI & Data Privacy
AI privacy, compliance, and data sovereignty for regulated environments. How to deploy frontier AI capabilities on infrastructure you control — without sacrificing performance or falling foul of GDPR and the AI Act.
[ READ → ]
// FROM_THE_BLOG
The Missing Piece of the Claude Code Workflow: Isolated Worktree Databases
JD Wuarin
OpenClaw and the Programmable Soul
Duncan Anderson
Building AI products means managing API costs. Here's what actually worked
Thibault Boutet
Building a Production Multi-Agent System for Document Writing
Thibault Boutet
Mean Pooling Beats Attention: Predicting Telomerase Activity from Whole-Slide Images
Kevish Napal
The Dimension Dilemma: Why 2.5D Models Outperform 3D CNNs for Stroke Classification
William Auroux
Understanding and Processing CT Imaging for Stroke Detection
William Auroux
Building a Reproducible Multimodal Pipeline
Kevish Napal
Understanding Cancer and Telomerase: From Biology to New Treatments
Kevish Napal
The 4 Levels of AI Agents: When to Use Workflows vs Autonomous Systems
Duncan Anderson
AI FROM THE
TRENCHES
Conversations with leaders who've actually led AI initiatives
Can a Foundation Model Read the Human Brain?
with Kris Pahuja from Piramidal
Can AI Save Scientists From Information Overload?
with Dr Oliver Bogler
From IBM Watson to Barnacle Labs: Lessons From Building AI Too Early
with Duncan Anderson and JD Wuarin
Inside Shopify’s Scout: The scrappy AI tool that went all the way to the boardroom
with Rich Brown from Shopify