Resilient AI architectures for real work contexts, from potential analysis through architecture and build to handover for in-house operation. Entry from €3,800 with the potential analysis.
Send inquiryAI implementation means designing, building, and handing over an AI system for real work processes. It is not about installing a tool, but about creating an architecture that fits your processes, roles, and system landscape.
AI initiatives in companies rarely fail due to lack of motivation. They fail due to lack of implementation. Either because nobody internally has the time to set up a system that carries through everyday work. Or because external vendors install a tool that misses the real processes.
Focus Institute works differently. We analyze your current situation, develop an architecture along your processes, roles, and system landscape, and implement it until the system runs in your house. No standard solution, no SaaS license, no workshop artifact. A system that fits because it was built for you.
Four phases, each of which enables a clear decision. You step in at each stage deliberately, not in one big commit.
An AI system running in-house, including architecture documentation, training of key people, and full operation. No SaaS lock-in, no dependency.
An AI implementation runs in 4 phases: potential analysis, architecture, build, handover. Entry from €3,800 via the potential analysis, then scope-dependent (typically 4–10 weeks for the build).
Not as references for sector fit, but as evidence of what is technically and organizationally possible. We think your solution from your context, not from these examples.
Weekly newsletter with depth, built on curated sources rather than quick AI surface
Individual transfer support without manual effort per participant
A calm list of relevant developments daily, instead of information overflow from 30 newsletters
Consistently high quality across repeated use instead of one-off work that restarts every time
The difference: training enables your people to build AI themselves. Implementation delivers a finished system on handover.
An AI implementation at our firm is not a quick shot but a structured build. It begins with a potential analysis, where we clarify the application case, work context, and relevant conditions. Based on that, we design a fitting architecture before implementation starts. In the end, the result is transferred into everyday work and, when needed, handed over for in-house operation.
The cost of an AI implementation depends on the application case, complexity, and desired scope. The entry is through the potential analysis for €3,800. It provides a solid basis for deciding whether and how a project should be continued. Everything else follows from architecture, scope, and handover requirements, not from package logic but from actual need.
The duration of an AI implementation depends on the target picture, depth of coordination, and technical integration. Small, clearly defined projects can be structured significantly faster than complex setups with several stakeholders or systems. What matters is not showing something quickly, but building something that holds up in daily work. That is why we do not work with blanket promises but with a clean approach from analysis through architecture to handover.
The offer is cross-sectoral where knowledge work, communication, learning processes, decision support, or recurring workflows should be intelligently supported. It is particularly meaningful in environments where people are not simply looking for „just another tool" but for a solution that fits the actual work context. What matters is therefore less the sector and more whether a viable application case, clear conditions, and a real need for implementation are present.
Whether and to what extent access to data or internal systems is necessary depends on the specific application case. Not every project requires direct system access. Where access is useful or necessary, this is clarified transparently in advance and limited to the necessary extent. Questions of data protection, roles, permissions, and operating model therefore do not belong at the end but from the beginning in the architecture.
Implementation is aimed at organizations or decision-makers who do not primarily want to build their own competency but rather develop or have a concrete result implemented. Training enables people to use AI more substantively themselves. Implementation, by contrast, builds a concrete solution, architecture, or work logic.
Write to us via the contact form or directly by email. We respond personally, clarify your context in a first conversation, and suggest the right entry for you.
The first conversation is non-binding and personal.