// AI strategy for companies
AI strategy
with roadmap and prototype.
Many AI projects fail because nobody decided early which use case matters and which data it needs. We develop AI strategies for mid-sized companies and enterprises that end with an actionable roadmap and a prototype built on real data. Consulting and implementation come from one team.
// The Problem
Why AI projects
fail without strategy.
Our team has built 10 AI systems that run in production, across 6 industries. Along the way we have seen where projects typically stall.
Wrong Use Cases
Technically interesting but irrelevant to the business. Without measurable ROI there is no stakeholder buy-in.
Missing Data
No data governance, poor quality, siloed systems. AI depends on data, and many companies are not ready for that yet.
No Organizational Readiness
Missing skills, resistance to change and no mandate from senior management. Technology alone does not solve organizational problems.
Tool Chaos
Ten departments each run their own AI tool, with no integration between them. Without a technology strategy, individual experiments pile up and never form a working system.
// Our Framework
From readiness
to production in 6 steps.
AI Readiness Check
Where does your company stand? We look at processes, data, team and tech stack, and identify blockers before anything gets built.
Use Case Discovery
In a workshop with your team we find out which processes take the most time, where the data sits and what would have the greatest impact. We prioritize by business value relative to implementation effort.
Technology Decision
Open source or commercial? Self-hosted or cloud? Which LLMs, tools and architecture? We decide based on your requirements, independent of vendor partnerships.
Prototype Sprint
The most important use case becomes a working prototype within 2-4 weeks, built with real data, real APIs and measurable results.
Roadmap & Scaling Plan
A phased plan shows which use cases come next and what budget and resources they need. It includes milestones, KPIs and a governance structure for the next 12-18 months.
Implementation Support
We stay involved through AI consulting, agent development, automation and workshops. Strategy and execution come from the same team.
// Where Are You?
Three maturity levels,
each with a path to production.
Curious
"We know AI is important, but don't know where to start." You need: AI Readiness Assessment, use case workshops, first orientation.
Piloting
"We've tried individual tools, but nothing is in production." You need: strategic prioritization, prototype sprint, technology consolidation.
Scaling
"We have first AI systems running and want to scale." You need: architecture review, multi-agent strategy, team enablement, governance.
// Deliverables
What you get
from our strategy.
AI Readiness Report
We assess where your company stands today, where its strengths and gaps lie, and which actions follow from that.
Use Case Portfolio
Each use case is prioritized by impact and effort and comes with its technical requirements, data needs and estimated ROI.
Implementation Roadmap
A 12-18 month plan with phases, milestones, budget and resource requirements turns your AI strategy into concrete steps.
Technology Blueprint
We document architecture decisions, tool selection, the integration plan and a GDPR compliance check. This forms the technical foundation for all future AI projects.
Working Prototype
A functional AI system for the use case with the greatest impact, running on your infrastructure.
Executive Summary
A summary for the executive board that covers the business case, ROI projection, risks and next steps. It is written for board presentations and budget approvals.
Every strategy engagement ends with working code that your team can test.
// FAQ
Frequently Asked Questions
About AI Strategy.
What is an AI strategy?
An AI strategy defines which use cases deliver the most business value, which technologies to use, what data is needed and how the organization has to develop. It is a business plan that uses AI as a lever.
Why do many AI projects fail?
Many AI projects never reach production. The most common causes are use cases that are technically interesting but irrelevant to the business, missing data (quality, access, governance) and a lack of organizational readiness (skills, resistance to change, no mandate from senior management).
How long does an AI strategy take?
AI readiness assessment: 1-2 weeks. Strategy with roadmap: 3-4 weeks. With a first prototype: 6-8 weeks. We work iteratively and test assumptions early.
What does an AI strategy cost?
An AI audit with use case portfolio and roadmap starts at EUR 5,000. We build the prototype in sprints of 2 to 4 weeks at EUR 8,000 each, plus a one-time setup and discovery phase from EUR 5,000. The final budget depends on company size and scope.
Does a mid-sized company need an AI strategy?
Yes, especially there. Without a strategy, budget goes into the wrong tools and use cases. With one, you start with the use case that has the greatest impact, see early results and scale step by step.
How are you different from large consulting firms?
The same team that develops your strategy also builds the working prototype. You receive a strategy document of about 20 pages and a system you can test.
// Next step
Your AI strategy
starts with a call.
30-minute discovery call, free of charge. We assess your AI readiness, identify the use case with the greatest impact and outline the path to production.
Book a discovery call