Dansen AI is working with Radnik Exports in the discovery and pilot preparation phase of an operational intelligence deployment. The engagement is focused on workflow visibility, data mapping, and scoping the first live operational use case for an MVP — not on delivering a finished system.
What does the discovery phase cover?
This phase is intentionally scoped around understanding before building. It includes workflow understanding across order, procurement, and production flows; system mapping across the tools and data sources Radnik currently operates through; structured data collection from those sources; and the definition of a first live operational use case that the MVP will address.
Why scope before building?
Because a system built on an assumed workflow will encode the assumption. The goal of discovery is to produce a precise operational picture of where decisions are currently made, where they slip, and where an intelligence layer can create measurable clarity. We are prioritising credibility over velocity.
How does this work alongside existing systems?
Our working approach is consistent with how Dansen AI deploys elsewhere. We do not replace Radnik’s existing systems. We are mapping them, modelling the relationships between entities that move through them — orders, materials, approvals, communications — and preparing a live decision surface that can sit on top of the stack without disruption.
What happens next?
This note will be updated as the engagement moves from discovery into the pilot build phase. Subsequent notes will cover the scoped MVP, the first live operational use case, and the measurable outcomes we agree on with Radnik before any live deployment begins.