Decide.
AI strategy & ROI
Which application deserves your investment? We assess potential, feasibility and total cost.
- Prioritised use cases
- Business case & success criteria
Your AI investment
must pay off.
For businesses ready to put AI to work: we establish the value, build the right solution and give your team the skills to use it.
Discuss your AI initiativeStart with one process, one pilot or one business goal.
A real person to work with.
From goal to handover.
You work directly with Matthias Grabner. I connect the commercial question with the technical delivery and the work your team does.
My work brings together software engineering, automation and AI training. Experience across Europe and Korea shapes how I approach technology, collaboration and change.
The best solution is the one that helps your team in their daily work.
Before our first conversation.
Do we need a fully defined use case?
No. A business goal, a recurring bottleneck or an existing pilot is a good starting point. Together, we establish whether and where AI makes sense.
Can you improve an existing solution?
Yes. We review its current state, quality and integration to establish what is missing for the next step or a wider rollout.
What stays with our team?
Knowledge, working materials and clear responsibilities. Training and, where useful, internal champions support independent use and further development.
Turn an idea into
something you can test.
Three possible starting points. See how the work changes, what you receive and how to assess the value.
Illustrative applications, not client projects. Value and feasibility are tested against your cases.
From scattered documents to a proposal you can review.
- Today
- Experts piece together requirements and evidence from scattered documents.
- With AI
- A draft brings together requirements, relevant content and sources. Experts review commitments and prices.
- Your working material
- A requirements matrix, proposal draft and a list of missing evidence.
- Success criteria
- Time to approval, completeness and expert review effort.
The right support.
For your next step.
Three areas of work, one shared goal: an AI application that holds up in daily use. Start where you need support or work together through delivery.
Enable.
Training & rollout
Give your team the skills to use and develop the solution. With exercises based on their own work.
- Practical workshops & rollout support
- Internal champions & Train the Trainer
Build.
Implementation & automation
Turn a clear brief into a working solution. In your processes, with your data and systems.
- An integrated, expert-tested pilot
- Approvals, monitoring & operational handover
Understand AI.
Put it to work.
Three practical workshop formats, shaped around your team, your experience and the task ahead.
Use Case Sprint
From a team workshop to a testable MVP.
Bring business and technical colleagues together around a real task. We identify and prioritise use cases, map the data, processes and systems involved, then build a first working prototype (MVP).
Testing it against agreed criteria shows what is feasible and what still needs work. Your team learns what AI can do and what it takes to make it useful.
- What you leave with
- A testable MVP, a map of the data and workflow, and evidence for the next investment decision.
AI Foundations
A shared starting point for your team.
Understand how generative AI works, where it helps and where it needs checking. Through examples and exercises from everyday work, your team practises prompting, providing useful context and judging results.
- What you leave with
- A shared understanding of AI, practical working methods and relevant ideas for your team.
Agent Engineering Lab
From using AI to building agent workflows.
For teams already working with AI. Build an agent prototype and explore context engineering: how instructions, knowledge, tools and state shape its behaviour.
Then use harness engineering to design the execution environment, permissions, evaluations, monitoring and points for human intervention.
- What you leave with
- An agent prototype, an evaluation plan and a clearer path to reliable operation.
A clear path.
Four steps together.
A manageable process. After each step, we know what makes sense next.
Define the goal
Agree on the task, baseline, owners and success criteria.
Outcome: a clear brief
Test at a small scale
Evaluate a pilot against typical and difficult cases for quality and effort.
Outcome: an informed decision
Make it part of the work
Integrate the solution, establish approvals and help your team get started.
Outcome: a usable workflow
Measure the impact
Adoption, quality, costs and business results show what works and what needs to change.
Outcome: a reasoned next step
One process.
One pilot.
Your next step.
Tell me what your team wants to understand, build or decide. Together, we’ll find the workshop or consulting format that fits your starting point.
Discuss your AI initiativeA short description is enough.
office@grabner.tech