For System Integrators, and for anyone who delivers system integration: new tools, new methodology, results-based delivery. Ours already works this way.
Born among System Integrators, grown alongside companies: we work with the people who build systems, run them and use them.
Practices that deliver SAP and integration programs for clients and need to protect margins while days deflate.
Competence centers and internal delivery teams that want AI-based delivery without waiting for a vendor roadmap.
Functions that want AI inside their processes, not in their slides.
Value concentrates in the middle: experienced people who direct the AI and judge its work. That is where the margin is built, and where investment and attention go. The pressure has already started: clients ask for a discount because you use AI, whether you really do or not.
AI changes how results are priced, how people learn the work and how quality is verified.
Today, time and materials or fixed price, the number still comes from estimated days. With days deflating, price anchors to the result and to the risk you take on.
The operational work juniors learned on is absorbed by the AI. The pipeline of tomorrow's seniors is rebuilt around judgment, on real decisions, or you keep hiring analysts for a pyramid that no longer exists. A junior produces a handful of analyses by hand each year, to build a yardstick, and validates many more produced by the AI.
Today's controls live on hand-off documents and end-of-phase signatures. Many of those documents lose their reason to exist; others become live views generated from the work. Control moves to continuous validation: what is covered, what is verified, who answers.
We don't do traditional consulting. We start AI-based.
Teams cannot stop delivering while they redesign how delivery works. We work alongside real projects, introducing AI one verified activity at a time. Coverage keeps the perimeter visible; evidence determines when control can change.
We observe how the work is really done: where time is spent, where judgment sits, which dependencies matter and what the system must be able to do.
What remains: a shared perimeter and coverage map version zero.
AI works in parallel with the team on a real delivery stream. It prepares configuration, developments, tests and knowledge assets while the existing delivery continues.
What remains: measured evidence of where AI accelerates the work without weakening control.
Where evidence supports the change, AI-generated work enters the delivery flow. Human validation remains explicit and the coverage map is updated after every verified cycle.
What remains: a controlled operating model built through use, not imposed by decree.
Proven patterns become reusable capabilities. The method extends to other process areas, teams and projects, while reviewers are trained directly on real work.
What remains: a scalable delivery capability and a new pipeline of expertise.
From one controlled use case to a reusable delivery capability. Evidence before scale.
We introduce AI into real work progressively. Each activity earns its level of autonomy through verified results, with clear responsibilities and human oversight.
The switch all or nothing
Our dimmer one activity at a time; each notch earned
a sample of the output always stays with a person, at every notch: it is how we know the trust signal tells the truth
The dimmer sets how much the AI does on its own. Responsibility stays explicit; the controls change shape.
More programs without proportional hiring, margin on fixed-price and outcome-based contracts, a product asset in bids instead of bodies, and a rebuilt pipeline of seniors.
The same model applied to your competence center: personalizations seen working while the analysis is still open, controls that transform instead of disappearing, people who grow faster.
MOSAIC inside the delivery: a senior virtual SAP consultant alongside each of yours, at every phase from assessment to AMS. From the platform as it is to co-branded components: the technology choice can wait for the pilot numbers.
No. We work alongside System Integrators and feed your governance tools with structured outputs. TFB doesn't replace your systems; it makes your people more effective in working with them.
We don't sell days of effort and we don't staff a pyramid. Every engagement starts AI-based: experienced people direct the AI and judge its work, delivery is priced on results, and AI autonomy grows only on verified results.
In advisory, no: your team delivers, with our model, and we stay alongside the people who deliver without taking over the delivery. Where we deliver programs ourselves, we say so explicitly and we work in co-delivery with partners where that is the right setup.
On a defined perimeter. Diagnosis and accompaniment come with objectives, scope and fees defined up front, measurable and reversible.
The documents that only translated between specialists disappear. Coverage and verification artifacts become central. Many documents become live views generated from the work. Human decisions, physical events and responsibilities stay exactly where they are.
Two to four weeks. We look at how your team actually works, where the hours go and where the judgment sits, and we pick the first ground for a pilot together.
Tell us what is heavy today. We reply within two working days with a first read and, if it makes sense, a slot for a call.
