3. The DEX analysis
The DEX Analysis – Clarity About Your Organization
The DEX Analysis (Digital Experience & Execution) is the foundation of every successful AI implementation with Vimmera AI. It creates an objective, reliable picture of how your organization actually works – not just on paper, but in real everyday life.
After the analysis meeting, we can, if you wish, jointly conduct a complete DEX analysis of processes and workflows in your company or organization. In doing so, we achieve a significantly higher level of detail than in the analysis meeting.
While many projects are based on assumptions, individual opinions, or isolated process descriptions, DEX captures the entire work reality: information flows, processes, systems, interfaces, sources of knowledge, and human working methods are considered together and put into a clear context.
What is the DEX Analysis for?
The DEX Analysis answers two central questions:
Where does AI deliver the greatest benefit in your organization?
What is the actual benefit in my company after implementation?
To this end, it makes visible,
- where time is lost,
- where processes come to a halt,
- where knowledge is tied up or hard to access,
- where errors, queries, or media disruptions arise,
- and where existing systems support or hinder.
This creates a realistic, unvarnished picture of your organization – free from gut feeling and individual perspectives.
The results of the DEX Analysis serve as an objective reference for you and us. It forms the starting point against which the impact of the AI solutions introduced later can be measured. After implementation, we conduct the DEX Analysis again and compare the “before” state with the “after” state.
This way, it becomes visible what concrete benefits the AI implementation has actually brought – and in which areas there is further optimization potential.
What happens in the DEX Analysis?
In the DEX Analysis, we bring together all relevant information sources in your organization: data from existing systems, documents, process descriptions, work instructions, employees’ experiential knowledge, as well as the actual workflows in everyday life. In doing so, we not only look at how processes are theoretically defined, but how they are actually lived in practice.
We analyze how information flows through your company, where it originates, how it is passed on, and where it may be lost or processed multiple times. We also look at how decisions are made, what dependencies exist, and where delays, queries, or uncertainties occur. This also reveals hidden friction losses that are often not visible in classic process descriptions.
The result of this analysis is a structured DEX reference – a transparent, detailed image of your current actual state. It clearly shows how your organization works today, where strengths lie, and where potential is hidden. This reference forms the objective basis for all further steps and makes it possible to evaluate the impact of the AI solutions introduced later in a measurable and comprehensible way.
What you get from it
The DEX Analysis creates security at all levels. It prevents AI from being introduced on suspicion, under pressure, or based on gut feeling. Instead, it ensures that every measure is based on a well-founded, objective basis and is targeted where it can have the greatest actual effect.
This gives you a clear prioritization of sensible areas of application: it becomes visible which processes, tasks, or areas of knowledge can particularly benefit from AI – and which cannot. At the same time, a reliable basis for decisions regarding investments, organizational changes, and technological directions is created.
In addition, the DEX Analysis creates an objective starting point for later success measurement. Thanks to the defined actual state, it is possible to precisely track which improvements have actually been achieved after the introduction of AI – in terms of time, quality, stability, relief, or productivity.
At the same time, you gain transparency about your own processes, information flows, and knowledge structures. Many connections, dependencies, and bottlenecks become visible and comprehensible for the first time – not as individual opinions, but as a structured overall picture.
This way, AI does not become an experiment, but a controllable, economically sensible tool that is used precisely where it really strengthens your organization.
In short
The DEX Analysis makes visible where your company stands today –
and creates the basis for using AI in a targeted, measurable, and responsible way.
1. The introductory meeting
The introductory meeting – the first step towards effective AI The use of artificial intelligence in companies does not begin with technology, but with understanding.That’s why every collaboration with Vimmera AI starts with a structured introductory meeting. This meeting serves to truly understand your organization, your challenges, and your goals. It is not a sales […]
2. The analysis discussion
The analysis meeting – from understanding to structure After the introductory meeting, the next decisive step follows: the analysis meeting.This is no longer about a first mutual introduction, but about a systematic, joint understanding of your organization. In this meeting, we begin the structured company analysis based on DEX (Digital Experience & Execution) – the […]
3. The DEX analysis
The DEX Analysis – Clarity About Your Organization The DEX Analysis (Digital Experience & Execution) is the foundation of every successful AI implementation with Vimmera AI. It creates an objective, reliable picture of how your organization actually works – not just on paper, but in real everyday life. After the analysis meeting, we can, if […]
4. The knowledge collection
The collection of company knowledge – making everything visible Before AI can use, understand, and reliably provide knowledge, this knowledge must first be fully and correctly captured. That is precisely why the systematic collection of company knowledge is one of the most important steps on the way to an effective AI solution. This is expressly […]
5. Data preparation
Data preparation – from raw material to networked corporate knowledge Once the corporate knowledge has been fully collected, the step begins that decisively determines how powerful, reliable, and useful the later AI will actually be: data preparation. In this phase, a large number of individual files, texts, media, system extracts, and experience reports are, for […]
6. The data verification
Data Verification – Creating Trust in Knowledge and AI After company knowledge has been collected and structured, cleaned, and linked together during data preparation, the step follows that turns information into truly reliable knowledge: data verification. In this phase, it is decided which content may actually be considered valid, binding, and actively usable. Because even […]
7. Data embedding and data vectorization
Embeddings & vector search – enabling AI to find and use knowledge precisely After knowledge has been collected, processed, and verified, the next step ensures that the AI can later access this knowledge quickly, precisely, and in the right context: chunking, embedding, semantic processing, and the creation of vector databases (vector stores). This step is […]
8. The selection of the LLM or LLMs
The selection of LLMs – the right AI brain for your tasks After knowledge has been structured, verified, and technically prepared so that it can be found and used precisely, the next central step follows: the selection of Large Language Models (LLMs). LLMs are the “thinking machines” behind AI – they determine how language is […]
10. Implementation of security mechanisms
Additional security mechanisms – protection for knowledge, systems, and results In addition to selecting and combining the appropriate LLMs, another important step is implemented depending on the requirements and area of application: the implementation of additional security mechanisms. Because your knowledge is valuable, and it deserves the same protection as any other business-critical system. Vimmera […]
9. Prompt Engineering
Prompt Engineering – Giving AI a Clear Identity After the company knowledge has been collected, processed, and verified, another central step follows: prompt engineering. In this phase, it is determined how the AI thinks, responds, and acts. Vimmera AI takes this step in close coordination with you, because this is not about technology, but about […]
11. Additional data sources and interfaces
In addition to the knowledge base from documents and verified company knowledge, it may be useful or necessary—depending on the application—to connect additional data sources. This includes the additional implementation of databases, business systems, and other data interfaces, for example via modern integration standards such as MCP. The background is simple: Not everything an AI […]
12. Customization of the user interface
Frontend & User Interface – AI where people really work For AI to be effective in a company, it is not enough for it to work technically. It must be available where employees actually work – simply, reliably, and without additional hurdles. That is why Vimmera AI generally relies on browser-based frontends. Browser-based solutions offer […]
13. Rollout of the AI systems
Rollout & Introduction – Bringing AI into Everyday Work Step by Step After all technical, content-related, and organizational foundations have been established, the rollout phase begins. In this step, the AI is not simply “activated,” but is introduced into real everyday work in a controlled, guided, and coordinated manner. The goal is for the AI […]
14. Change Management
Change Management – Safely Guiding People Through Change The introduction of AI is not just a technical project, but a profound organizational and cultural change. New systems, new ways of working, and new possibilities trigger uncertainty, questions, or even fears in many people. Vimmera AI knows this – and that is precisely why change management […]
15. Fine-tuning before the actual launch
Joint fine-tuning before go-live – ensuring quality before it counts After AI has been introduced in initial teams or departments, a targeted phase of joint optimization, adjustment, and error correction follows – even before the system goes live company-wide. This phase is crucial to turn a functioning solution into a truly robust, practical AI. Pilot […]
16. Go-live
the productive start of your AI After the successful pilot phase and joint fine-tuning comes the decisive moment: the go-live. In this step, the AI is officially activated for productive use within the entire defined scope. From now on, it is no longer just a pilot project, but a permanent part of your working environment. […]
17. The second DEX analysis
Measure impact, identify potential, develop in a targeted way After the go-live, the phase begins in which it is decided whether AI has not only been “introduced” but has actually become effective. This is exactly why the DEX analysis is carried out a second time. It is not a formal conclusion, but a deliberately set […]
18. Care, support & further development
so that your AI remains valuable in the long term With the go-live and the second DEX analysis, the AI has successfully arrived in your company. But just like your company itself, your AI does not stand still. Products change, processes are adjusted, new insights emerge, markets and requirements continue to develop. At the same […]
19. Documentation
Transparency, Security and Long-Term Usability A professional AI system is only as good as its traceability. That is why documentation at Vimmera AI is not a by-product, but a central component of every solution. It ensures that your AI system not only works today, but also tomorrow, in a year, and in a changed organizational […]