Engineering situation

Integrate Data, ML or AI into information systems

Add new capabilities without creating a technological silo or bypassing the existing architecture.

What we examine

We primarily work where these capabilities need to be integrated into a real information system: data, APIs, permissions, security, performance, observability and production deployment. AI is not treated as an isolated demo.

Possible interventions

Discover our approach

Choosing a model is an architecture decision. Compare quality, cost, latency, privacy, hosting constraints, maintainability and reversibility.
RAG, prompting, specialised models, rules, lightweight adaptation and fine-tuning address different problems.

Explore

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Engineering continuity.

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