Just learned about the RAG Playground in Elastic, so I am hoping this is an opportunity to simplify my project:
Here is my scenario / goal:
We have an old rules-based app that parses store items like bikes, bike parts, etc. (It could be other products, and each product would have it's own domain/training)
Our historical data is already in elastic indexes - so we have a large dataset we can use to train against.
What I would like to do is replace the rules-based app with an AI-based process that would be more accurate, and ultimately faster.
So the workflow would essentially be -> read a piece of text or small json file that comes in as input -> LLM parses it into json using a defined schema for the product domain (using our existing indexes as trained data) -> then match it using elastic to a known catalog of items (also in elastic). if i could skip the "output it in a json format" and just go and match it against the catalog, that would probably be better but my thinking was there needs to be human review / training / prompt writing / rules updates that needs to happen to perfect the training/matching. I would l have a custom built “workbench” for this using elastic api’s.
Would love thoughts/feedback and some guidance about how to get started w/this.
Thanks,
Bob