Programme-level, evidence-first
Stop funding pilots and pick the two that should be systems
AI transformation work at TechFabric starts by finding which parts of the business would actually change if a system ran there, and then building those. We sequence a programme around what can be measured, retire the pilots that were never going to ship, and put governance under the ones that stay.
Most transformation programmes fund fifteen pilots and ship none. The pilots are not the problem. The problem is that nobody scoped which of them would still matter at production volume, under real permissions, with somebody accountable for the output.
- Who it is for
- Executives with a mandate, a budget, and fifteen pilots
- Bench
- 115+ engineers, 80 Databricks-certified
What we work through
- Every pilot in flight, and what it would take for each to reach production
- Which processes would genuinely change, measured against what they cost today
- The permission and data model, because it decides what is buildable at all
- Where accountability lands once a system rather than a person makes the call
- What the programme costs to run, not just to build
What you get
- A ranked shortlist: what to build, what to stop, and the reasoning for both
- A sequence where each phase pays for the next rather than deferring value to the end
- The governance model underneath, so the systems can be defended to risk and audit
- Delivery of the first one, by the people who scoped it
FAQ
AI transformation: common questions
What does AI transformation actually involve?
Deciding which work should be done by a system, building those systems, and putting governance under them. The deciding part is where most programmes go wrong, because it gets done as a strategy exercise rather than against what is technically buildable in the platform and permissions you have.
How is this different from a management consultancy?
We build. The same people who scope the programme deliver the first system in it, which changes what gets recommended, because nobody proposes a phase they will personally have to explain in month six. If you want a strategy document and no delivery, we are an odd choice.
We already have a strategy. Can you just build?
Yes, and that is a good way to start. Bring the strategy, we will scope the first system against it, and if we think the sequence is wrong we will say so once and then build what you decided.
How do you measure whether it worked?
Against the number the process was already judged by, agreed before the build. Cycle time, cost per case, exception rate, whatever the business already tracks. A new metric invented alongside the system is how a programme reports success nobody feels.
The rest of our AI work
AI Readiness Assessment
Leaders with AI on the roadmap and no clear view of what is in the way
AI Tools Assessment
Finance and platform leaders holding a renewal they cannot justify
Agentic AI development
Engineering leaders whose agent pilot cannot get past review
AI workflow automation
Operations and engineering leaders with a process that half-completes
AI enablement
Engineering leaders whose team needs to own this, not outsource it