Everything after the pilot
European AI strategy and transformation for organisations of 100 people and up who want to do AI the right way. We work on the part that decides whether AI agents and use cases ever reach production.
Nearly every enterprise runs pilots. Almost none of them change anything.
The failure is not technical. Roughly 80% of the work in getting AI use cases into production is data engineering, governance, workflow integration and measurement. The parts that live in the organisation rather than in the LLM.
That is also why bringing in a specialist changes the odds so sharply. It is not better models or tools, but rather someone whose whole job is the unglamorous distance between a working demonstration and a system people actually use and trust.
- of enterprise AI pilots deliver no measurable P&L impact
- 95%
- success rate when a specialist vendor leads vs. 33% for internal builds
- 67%
- of companies abandoned most of their AI initiatives during 2025
- 42%
Source: MIT NANDA, The GenAI Divide: State of AI in Business (2025); S&P Global (2025)
Four stages run in sequence
BASE is one journey to AI adoption, not four distinct services. Each stage builds the trust and the input the next one needs and each is worth doing on its own. Your organisation as a whole, and teams within, will be at various stages of the journey, and we can help you progress until AI becomes a real differentiatior for your business.
Bootstrap
Awareness & champions
Hands-on awareness of what AI can and cannot do inside your organisation, and a cohort of internal champions who understand it well enough to carry it.
Align
Direction & scoping
Awareness turned into direction, through fixed-scope engagements rather than open-ended strategy work.
Shape
Building & optimising
Scoped ideas become agents and use cases running in production, assembled from a growing library of building blocks, rather than built every time from zero.
Evolve
Scaling & governance
The long-term relationship once capability exists and value has been proven, from portfolio scaling, governance, and continued upskilling as the organisation matures.
The hard part was never the LLM.
Strategy consultants hand over a deck. Development shops hand over a repository. Training companies hand over a certificate. Each is genuinely useful and none of them, on their own, gets an agent into production inside a complex European enterprise.
Solidbase does the three together because they are the same job: the strategy that decides what to build, the people who will own it afterwards, and the agents and use cases themselves. The method comes out of years of experience, first with cloud transformation programmes, then with data infrastructure, and now with AI use cases. We’ve delivered difficult projects for large, sometimes regulated, European organisations and now we’re applying our methodology to the era of AI.
European organisations
Delivery, data and inference stay in Europe. We build for EU AI Act obligations rather than retrofit to them once they bind.
100 people and up
Large enough that AI adoption is an organisational problem rather than a tooling one, which is the problem we actually solve.
High risk use cases
We have an inclination for use cases where security is paramount, and where the high-risk provisions of the EU AI Act apply.
Tell us where your AI programme actually is.
Let’s have a conversation about what you have running, what has stalled, and whether any of it is the kind of problem where our experience is useful.