Services · AI & Agents
Agents without process context automate the error. We implement AI agents that build on your process data, have an owner and whose effect we measure.
What it is about
An AI agent is software that does tasks in a process on its own. It checks cases, prepares decisions or triggers steps in your systems. To act correctly, it needs context: How does the process really run, which exceptions exist, which rules apply?
The topic covers
Many AI projects fail for an unglamorous reason: AI gets placed on top of work that nobody has really understood. AI scales whatever it finds. Point it at an unclear process and you do not get efficiency. You get the same mess, only faster and more expensive.
Companies that succeed with AI do the opposite. They first understand how the work really happens, and only then automate it. That is the whole craft. And it is the step many skip in the rush to add AI.
At WITTBIX, this step is Process Intelligence: We use your process data to show how the work really runs before an agent takes it over.
Study · Fraunhofer FIT and Celonis, 2026
This is the conclusion of the study “Enterprise AI schafft Geschäftswert” by Fraunhofer FIT and Celonis, published in July 2026: AI success does not depend on the best model. It depends on whether a company masters its business context and makes it available as a shared foundation. The study names five structural hurdles. WITTBIX addresses each of them.
| Hurdle named in the study | How WITTBIX addresses it |
|---|---|
| 1. Fragmented data and process foundationAI usually sees only fragments instead of end-to-end process chains. | Process Intelligence links process flows across all systems to KPIs and monetary values. Process Intelligence → |
| 2. No shared business contextTerms, objects, roles, rules and KPIs are rarely anchored in a common context layer. | Process Intelligence creates the context layer across all systems and processes so that AI can be used in a targeted way. Process Intelligence → |
| 3. Unclear operating model and governanceRoles are unclear, and decisions take longer than AI innovation cycles. | Governance and target operating model for your Center of Excellence: Roles, steering board, value tracking, quarterly business review. People & Change → |
| 4. Diffuse value logic and rising costsTarget KPIs are missing, and effects are rarely proven end to end. | No agent without a business case. Every agent has an owner, a number in euros and a baseline. Value → |
| 5. Weak change managementAI runs as an isolated technology project. | Stakeholder alignment from D1, training and support during implementation. People & Change → |
Around two-thirds of AI initiatives remain in pilot mode.
Source: Fraunhofer FIT and Celonis, “Enterprise AI schafft Geschäftswert”, July 2026, based on McKinsey & Company 2025.
Source: Fraunhofer FIT and Celonis, “Enterprise AI schafft Geschäftswert. Status quo, Werthebel und Umsetzungspfad” (German), July 2026.
Our offer
| Building block | What you get |
|---|---|
| AI context check | The process foundation and a business case for your sponsor. Same format as the D1 Pre-Evaluation. |
| Selection of agents | Tailored to each client, based on your process data and where the effect in euros is largest. No agent without a business case. |
| Implementation | We roll out the agents with our implementation partners. Your point of contact remains WITTBIX. |
| Measurement | Every agent has an owner, a number in euros and a baseline. |
One day, same format as the D1 Pre-Evaluation. Result: The process foundation and a business case for your sponsor.
Where Insights Turn into Business Impact & eXecution
Wittbix Value GmbH
Milchstraße 15 · 26123 Oldenburg
Germany
hello@wittbix.com
+49 179 7597905
linkedin.com/company/wittbix
www.doc-t.eu
Doc T initiates. WITTBIX realizes.
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