Why a retainer instead of project work?

Project work is ideal when scope and goals can be clearly defined. A retainer is the better choice once AI needs to deliver lasting impact, because the real effort begins after the first go-live: operations, monitoring, security updates, retraining and continuous improvements.

In classic projects, exactly these tasks often fall through the cracks or become the next add-on project. The result is stop-and-go, knowledge loss between phases, and systems that run but never mature properly. With a retainer, the topic stays in one hand throughout, priorities can be adjusted continuously, and AI systems are not just built but kept stable and continuously improved.

This works particularly well because AI initiatives always involve research and development, and not everything can be planned upfront. Instead of stacking change requests, work continues directly as soon as data, usage or requirements deliver new insights.