The primary challenge is not just about harnessing AI for search; it's about preparing complex documents of various formats, structures, designs, scans, multi-l

The primary challenge is not just about harnessing AI for search; it's about preparing complex documents of various formats, structures, designs, scans, multi-layout tables, and even poorly captured images for LLM consumption. This is a crucial issue. There is a 20 min read on why parsing PDFs is hell: https://unstract.com/blog/pdf-hell-and-practical-rag-applications/ https://unstract.com/blog/pdf-hell-and-practical-rag-applica... To parse PDFs for RAG applications, you'll need tools like LLMwhisperer[1] or unstructured.io[2]. Now back to your problem: This solution might be an overkill for your requirement, but you can try the following: To set things up quickly, try Unstract[3], an open-source document processing tool. You can set this up and bring your own LLM models; it also supports local models. It has a GUI to write prompts to get insights from your documents.[4] [1] https://unstract.com/llmwhisperer/ https://unstract.com/llmwhisperer/ [2] https://unstructured.io/ https://unstructured.io/ [3] https://github.com/Zipstack/unstract https://github.com/Zipstack/unstract [4] https://github.com/Zipstack/unstract/blob/main/docs/assets/prompt_studio.png https://github.com/Zipstack/unstract/blob/main/docs/assets/p...