01
AI strategy & roadmap
A durable roadmap that does not fall apart in the first architecture review. Prioritised initiatives with owner, budget and quarter - built with someone who has shipped the systems underneath.
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AI in production Access is governed.
Access is governed.
Sharing isn't.
An AI agent shares what it considers helpful - not what is permitted in context. Right person, wrong room. That is exactly what we control: Dissemination Control.
Based in Sweden - engagements across DACH, remote, on site for key meetings.
Industries from over two decades of engineering
- Rail transport
- Premium automotive
- Listed industrials
- Private banking
- Universal banking
- Asset management
- Medical technology
- Telecommunications
- Public safety
Practice
Five levers I usually pull.
I only take on work where I deliver more value than I charge. Engineering depth, not slideware.
02
Use-case discovery & prioritisation
A structured inventory across your functions. I score every use case on value, feasibility and risk - and tell you honestly which ones survive contact with production and which only look good in a workshop.
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03
AI governance & EU AI Act
Policies, processes and roles that hold up under audit from August 2026 onward. Sized for mid-market reality, not DAX compliance overhead - including the case where data must never leave your infrastructure.
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04
Training & enablement
From the leadership team to the developers who use AI every day. Formats that stick: ticket-based AI development, agent workflows, prompt and review discipline - not a one-off workshop forgotten after two weeks.
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05
Process automation & agents
End-to-end automation where the maths works. I design it, build it with your team and operate it long enough to prove it - with governance and audit trails from day one. No lock-in.
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Approach
Three phases. Nothing in between.
I
2–4 weeks
Diagnose
Interviews, code and architecture review, use-case inventory. Output is a shared picture of where AI moves the needle for you - and where it does not.
II
4–6 weeks
Design
Concrete initiatives, architecture options, a make-or-buy decision per case. We decide together; a steering committee signs off.
III
from 12 weeks
Deliver
I build and deliver the first one or two initiatives with your team - as lead architect or hands-on. Handover to a documented, operated, measured system.
The new reality
Capability used to be a question of company size. Not anymore.
With AI, a 100-person company now does things that would have taken a whole department five years ago: making sense of data, shipping faster, deciding better. What matters isn't the AI itself - it's whether it runs reliably, day in, day out, in real operation. That's exactly what I build. The projects below show how that looks.
Track record
Three projects. Decades of engineering behind them.
Selected engagements as lead architect, lead developer or senior business analyst - many of them turnaround mandates or critical first-time deliveries. I name them in conversation, under NDA.
Rail transport · 2021–2025
National rail operator, Germany
From monolith to microservices for a national rail operator
Card payment, ticket printing and signature capture, migrated from a monolithic application to 15+ microservices on Kubernetes/AWS. Over 100 REST APIs, 100+ ticket formats with precise layout control, millions of transactions in live operation. I led it as architect and lead developer - through every phase, from architecture through implementation to operation under high security requirements.
Outcome A monolith that slowed every change became a system carrying millions of transactions in live operation - maintainable, independently deployable, stable for years. What set the pace here wasn't the technology but the regulatory environment of a rail operator - exactly the brake that tends to be far smaller in a mid-sized company.
Spring Boot · Kubernetes/AWS · OAuth2/JWT · PostgreSQL · GitLab CI · Angular
Listed industrials · 2023–2024
Listed DAX industrial group
Workforce-planning platform with early LLM integration
Advisory and engineering for a workforce-planning programme with visibility up to top management. Data-processing logic for precise staffing decisions, a usable interface for genuinely complex HR data, a viable product strategy - and an LLM API integration where it actually paid off, not where it looked good on a slide.
Outcome Staffing decisions once buried in scattered spreadsheets now run through an interface that makes even the most complex HR data workable - with LLM support exactly where it pays off. A handful of people now make decisions at a quality that used to tie up an entire department.
Java · Spring Boot · Angular · Kubernetes · MongoDB · LLM-API
Premium automotive · 2018–2019
European premium car manufacturer
Music-streaming integration into a connected-car system
Concept and technical delivery of a global music-streaming provider's integration with the vehicle infrastructure. Direct alignment with the streaming partner, leadership of an international team, and accountability for timeline and budget.
Outcome Concept became a shipped feature in the vehicle - a clean interface to a global tech partner, aligned across borders, on time and on budget. Proof that integrating with a corporate giant needn't be a big-project risk when it's scoped right.
Apple Music API · RESTful Microservices · Java · Spring Boot · AngularJS · Git · Bitbucket · Google Cloud Platform (GCP) · AWS · Microsoft Azure · Jira · Confluence · Scrum · Kanban · Agile methods · DevOps
About
Andre Jahn
Independent AI Advisor · Jahn Consulting
An IT consultant, software architect and lead developer for German corporates and the mid-market for over two decades. No formal AI qualification - a career changer who learned AI by building production systems with it, not in a lecture hall.
My specialty is the projects on the brink of failure: turnarounds, migrations two other teams couldn't finish, systems that simply have to go into production. Before I came to AI, I built mission-critical software for rail payment, FDA-regulated medical data, public safety, premium automotive and private banks.
Today I bring that engineering discipline into AI projects. Taking GenAI from pilot to production is a technical discipline, not a rhetorical one - and that is exactly where most projects get stuck.
" No MBA, no slideware. Engineering depth is my only lever - and that is exactly the point.
Insights
What I'm currently publishing.
Notes from practice - and what I open-source.
Latest post · Enterprise AI
Recent The Line Item Missing from the Business Case
Business cases for AI automation weigh savings against running costs - and leave one real position unbooked: the loss of the fallback option. Why substitution isn't symmetric, which five paths lead to the same outage, why the ability to train people is the more uncomfortable case, and four measures that make the position quantifiable.
Read the post →
Open-source blueprint Dissemination Control for AI Agents
AI agents share what they consider helpful - not what is permitted in context. Dissemination Control closes that gap: vendor-neutral, building on your existing IAM, validated in a live reference environment. On GitHub, CC-licensed.
Read the blueprint on GitHub ↗
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The AI Is Not Your Friend
6 Aug 2026 -
Context Assembly Is a Governance Decision
26 Jul 2026 -
skill.md Is a Supply Chain
15 Jul 2026
Contact Let's talk about what
Let's talk about what
you're actually trying to do.
A 45-minute introduction - no sales pressure, no slides. I listen, give a first read, and tell you openly whether I'm the right partner.
Book an introduction →- GitHub
- github.com/JahnConsulting