AI strategy that in practice works
CodeGuides combines strategic AI analysis with direct development expertise. You won't receive a strategy report for the drawer, but rather a clear assessment: what's worth it, what's not, and how you can get started pragmatically.
- Use case analysis and prioritization according to ROI
- Technical feasibility and data situation checked
- AI roadmap with concrete MVP entry
- On request: direct implementation support from CodeGuides
Bring your processes and ideas with you - we will provide an honest assessment of what is really worth it.
- AI strategy with implementation expertise
- Medium-sized businesses & B2B focus
- Technical feasibility analysis
- From the roadmap to the MVP
Local AI or Cloud AI for companies?
Cloud AI is suitable for quick entry and non-critical data because it can be used without its own infrastructure. On-premise or local AI is the right choice for particularly sensitive data and high demands on data sovereignty. Hybrid models make sense for mixed requirements. The decision depends on data type, integrations, operational overhead and budget.
Do you want to process sensitive data completely in-house? Then leads On-premise AI continue. If it's about connecting models to existing software, see AI integration.
Why AI projects in medium-sized companies often not starting
Most companies know that AI could help them. The hurdle is rarely the technology — but rather a lack of clarity about priorities, feasibility and benefits.
Traditional management consultants create potential analyzes - but without a technical assessment of what can realistically be implemented in your system landscape.
Developers start with the first use case they come across without checking whether it really has priority, whether the data is available and whether the ROI is right.
ChatGPT licenses for everyone — but no plan: AI tools are used uncontrolled, without integration into systems and without a data protection concept.
There are ideas, but no decision: Which use case comes first, which is worth it, which is too complex to start with?
AI needs accessible, complete and structured data. Many projects fail because it is only noticed after the project has started.
Between strategy and development, there is a handover to a new agency that is not familiar with the analysis. Knowledge is lost.
Was KI Consulting in CodeGuides includes
We analyze, prioritize and plan - with the aim of being able to take over the implementation afterwards.
AI potential analysis
Systematic recording of your processes, data sources and system landscape. Where does real AI potential lie?
Use case prioritization
Clear recommendation as to which use case brings which ROI with what effort - and in which order you should start.
Technical feasibility
Which AI architecture is suitable? Which APIs, models and integrations are necessary? What is realistic in your infrastructure?
Data and system landscape
Is the correct data available? Are they accessible? Which system connections are necessary? Clarifying early will save costs later.
Business Case & ROI
Realistic cost and benefit estimates: What does the project cost, what does it save or generate, when does it start to pay off?
AI roadmap & MVP definition
Concrete plan: What will be built in the first pilot, in what time frame, with what budget? Including expansion perspective.
Here's how it works KI Consulting at CodeGuides
No long lead time, no vague strategy paper. The end result is clarity and an actionable plan - typically in 3 to 6 weeks.
Initial discussion & scope definition
Clarify goals, expectations, time frames and general conditions. Free, 45 minutes.
Process and system analysis
Capture the process landscape, system environment, data situation and existing integrations in a structured manner.
Use case workshop
Identify AI potential together, collect ideas and prioritize them in a structured manner based on effort, benefit and feasibility.
Technical feasibility analysis
For prioritized use case: Check architecture, model choice, data requirements, integrations and data protection.
AI roadmap & recommendation
Written summary: prioritized use cases, business case, MVP scope and recommended next steps — including implementation offer.
AI consulting that ends up in implementation - not in the drawer.
The difference to classic consultants: We develop ourselves. Our assessments are technically sound because we then build the same systems. No handover to an external agency, no loss of knowledge between strategy and development.
Who is it for KI Consulting suitable?
KI Consulting makes sense if you need clear direction before investing in development.
Well suited
- Medium-sized companies (50 to 500 employees) that want to approach AI strategically
- CEOs and executives who need to justify AI investments internally
- Companies with several AI ideas but no clear prioritization
- B2B software providers planning AI as a product feature
- Teams looking to restart after an unsatisfactory AI initiative
- Companies that need an initial honest assessment
Less suitable
- Companies with an already clear use case, available data and ready development capacity
- Very early exploration without a specific process or problem in the company
Unsure? In the initial consultation, we clarify whether consulting or direct use case advice is the better way to start.
Most AI projects fail not because of the AI, but because of a lack of preparation: unclear which process, unclear whether the data is there, unclear what it costs. That's exactly what we clarify in consulting - before a line of code is written.
Alexander Hähnel · CodeGuides GmbH
More AI services from CodeGuides
Consulting is the starting point. CodeGuides accompanies you from strategy to productive AI solution.
AI consulting for companies
Use case analysis and technical feasibility check for your specific process.
Learn moreAI automation agency
Automate manual processes: documents, emails, ERP connections and back office workflows.
Learn moreAI On-Premise
Local AI without cloud — GDPR compliant, self-hosted, no data transfer to external servers.
Learn moreHave an AI chatbot developed
AI assistant with your own company data, access rights and source information.
Learn moreFrequently asked questions about AI consulting
What is AI Consulting?
KI Consulting includes the strategic analysis of AI potential: identification of sensitive use cases, assessment of technical feasibility, business case calculation and creation of a concrete AI roadmap. It's about clarity and prioritization before investing.
What is the difference between AI consulting and AI consulting?
KI Consulting refers to the strategic level: Where and how should the company invest in AI, with what ROI and in what order? AI advice at CodeGuides often means the operational-technical level: Which specific process is suitable, which data is available? We combine both areas.
How much does AI Consulting cost at CodeGuides?
A compact AI consulting workshop with analysis, use case prioritization and roadmap typically costs between 3,000 and 8,000 euros, depending on the scope and depth. The free initial consultation is always the first step.
How long does an AI consulting engagement last?
A compact AI consulting project typically lasts 3 to 6 weeks: initial discussion, current analysis, workshop, feasibility check and strategy paper. Deeper analyzes or multiple business areas require correspondingly more time.
Does CodeGuides also take over the implementation after consulting?
Yes. This is a key advantage: no strategy paper that you have to hand over to an external agency. If the consulting shows that an AI project makes sense, CodeGuides can go straight into development. This saves frictional losses during the handover.
What size company is KI Consulting suitable for?
Primarily for medium-sized companies with 50 to 500 employees as well as B2B software providers that want to use AI strategically but do not yet have a clear plan.
Can I start without comprehensive consulting?
Yes. If you already have a specific process in mind, CodeGuides can start directly with a use case analysis. The initial consultation shows whether a quick check or comprehensive consulting is the better way to start.
Which industries does CodeGuides know particularly well?
Manufacturing industry, mechanical engineering, logistics, service companies and B2B software. Our AI projects cover documents, ERP integration, quality processes and internal knowledge management systems.
What is an AI roadmap?
An AI roadmap determines which AI use cases should be implemented in which order - with budget, expected benefits and MVP scope. It is the result of the consulting process and the basis for decision-making for the next steps.
CodeGuides is an app and AI agency from Germany for Flutter apps, custom software, AI automation and local AI infrastructure. Consulting and implementation come from a single source: We evaluate use cases technically, build the first pilot and scale it up to company-wide operation, GDPR-compliant and with hosting in Germany.
Request KI Consulting
Briefly describe your initial situation. In the initial consultation we clarify whether consulting or direct advice is the better way to start.
Arrange a meeting
45 minute initial consultation on your AI strategy and use cases.
Was passiert danach?
Choose an appointment in the calendar