AI + your own documents
Can find, summarise and phrase information.
Why DyReP
Searching and answering with your own company data is useful. This is often called RAG: retrieval-augmented generation.
For professional work, other questions remain: what applies now, which way of working belongs to it, which exception counts, who may decide and how can the result be checked afterwards?
This matters even more for AI agents that carry out tasks themselves. The more AI does by itself, the more important it is to set out what it may do.
A historical source can be right in substance and no longer apply today.
The conflict must remain visible until an authorised person has decided how to address it.
A document does not say by itself which steps, criteria and stopping points lead to a usable result.
Read access gives neither AI nor an employee the right to decide or publish.
A good summary can lose exactly the caveat that decides the matter.
A representation must not sound more certain than the knowledge it rests on.
A knowledge base holds your organisation’s knowledge. RAG retrieves relevant information from it. For professional work, that is not enough on its own.
Can find, summarise and phrase information.
DyReP sets up your knowledge as a managed knowledge base and also organises how that knowledge may be used in professional work. For work where mistakes carry weight, the working layer can act as a harness: the fixed boundary around AI that determines which knowledge and actions are permitted and where a person has to decide.
This brings together, among other things:
Neither replaces professional skill.
Above all, DyReP shows where professional skill is still needed.