Automated High-Quality Document Analysis

Description

In the realm of information overload, the ability to swiftly and accurately dissect complex documents is more vital than ever. This GPT transcends the current barriers of RAG-based document analysis. This tool is not just a mere summarizer; it’s an in-depth analyzer, capable of understanding and articulating the nuances of extensive documents by exploiting a complex tool chain. Designed for those who grapple with the daunting task of digesting lengthy reports, legal documents, or scholarly articles, this AI assistant ensures that no critical information slips through the cracks.

Intended Usage

Required Input: User-Uploaded Document

This GPT is engineered for scenarios requiring a deep dive into complex documents. Whether it’s a lawyer analyzing legal texts, an academic researcher sifting through dense papers, or a business professional evaluating comprehensive reports, this tool stands as an indispensable ally. It excels in providing a clear, concise, and accurate summary of even the most intricate documents, transforming hours of reading into minutes of insightful comprehension.

Works best for documents with coherent structure, and will dive into each section of importance for a granular and comprehensive understanding. Due to the complexity of this workflow, it can take multiple full responses to finish for complex documents. For more efficient or strategic workflows there are GPTs later in this portfolio tailored for that purpose.

User Commands

• !start – Initiates workflow based on user uploaded document.
• !demo – Demonstrates the workflow with synthesized data
• !continue – Continue the automated workflow.
• G – Synthesize the final report outside of the python tool with well-formatted markdown
• R – Restart the analysis with a new document.
• E – End the current analysis session.

Important Notes

• ENSURE the uploaded document shows DOCUMENT, and NOT PDF. This workflow requires RAG to operate correctly and currently only a small amount of PDFs actually work properly with RAG.
• If the workflow starts with a call to the python tool instead of a RAG search, thats how you know that PDF is unable to be vectorized or searched with RAG and this workflow will NOT work in that case. Doc and txt files work perfectly, you can use Adobe Acrobat to covert any pdf to a doc in about 3 seconds total.