Services
Pragmatic AI Usage
AI is everywhere in technical discussions today. Very few projects extract measurable value from it. My role isn't to 'add AI'. It's to help decide whether AI is relevant, where it actually is, and how to integrate it without weakening what already works.
When to Intervene
- internal or market pressure around AI
- uncertainty about real use cases
- concerns about costs, dependencies, or risks
- integration considered in an existing product or architecture
What I Do
- identification of use cases where AI brings concrete, measurable value
- cost, value, and risk analysis (quality, dependency, security)
- architectural framing and integration paths (orchestration, data, systems)
- definition of clear technical and organizational safeguards
What I Don't Do
- integrate AI "to follow the crowd"
- sell unrealistic promises
- build opaque or uncontrolled systems
What You Get
- a clear decision on using (or not) AI
- a controlled integration path if it makes sense
- less technical and cognitive debt
- a sustainable and understandable approach
For Whom
- CTOs and Tech Leads under pressure to integrate AI without clear framing
- Product teams who want to assess relevance before building
- Projects with an existing stack to preserve
- Organizations that want safeguards, not hype
AI entering your roadmap?
Tell me about your context, the use cases you're considering and your constraints. We'll frame it together.