Knowledge acquisition for retrieval augmented generation system

A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method of transforming data, the method comprising:

• receiving, at a retrieval augmented generation (RAG) knowledge acquirer, data from a local small foundation system and a centralized large foundation system, wherein:
• the RAG knowledge acquirer is connected to an enhanced distributed RAG system and the local small foundation system which are located on an edge site of a plurality of edge sites,
• the plurality of edge sites are connected to a centralized system to form an artificial intelligence (AI) hybrid distributed inference system, and
• the centralized large foundation system is located on the centralized system with a external information repository;
• making a determination that the data reaches a threshold for optimization;
• in response to the determination, processing the data to generate enterprise data for the enhanced distributed RAG system;
• transmitting the enterprise data to the enhanced distributed RAG system, wherein the enterprise data includes elements produced locally on the edge site by classifications from the local small foundation system and elements produced centrally at the centralized system by classifications of the centralized large foundation system;
• processing a copy of the data into master knowledge data;
• and
• transmitting the master knowledge data to a centralized master knowledge service base of external information repository.

A retrieval augmented generation (RAG) knowledge acquirer, comprising:

• a processor;
• storage comprising instructions, which when executed by the processor perform a method, the method comprising:
• receiving, at the RAG knowledge acquirer, data from a local small foundation system and a centralized large foundation system, wherein:
• the RAG knowledge acquirer is connected to an enhanced distributed RAG system and the local small foundation system which are located on an edge site of a plurality of edge sites,
• the plurality of edge sites are connected to a centralized system to form an artificial intelligence (AI) hybrid distributed inference system, and
• the centralized large foundation system is located on the centralized system with an external information repository;
• making a determination that the data reaches a threshold for optimization;
• in response to the determination, processing the data to generate enterprise data for the enhanced distributed RAG system;
• transmitting the enterprise data to the enhanced distributed RAG system, wherein the enterprise data includes elements produced locally on the edge site by classifications from the local small foundation system and elements produced centrally at the centralized system by classifications of the centralized large foundation system;
• processing a copy of the data into master knowledge data;
• and
• transmitting the master knowledge data to a centralized master knowledge service base of the external information repository.