Have you ever struggled with messy, unstructured documents, wishing you had a way to turn them into clean, structured data? Well, I’m excited to share an innovative solution with you: an open-source AI agent that does just that.
The concept is simple yet powerful: upload multiple documents of any type, and the AI agent will convert them into structured data in CSV tables, making it easy to visualize and work with your information.
So, how does it work?
The approach involves three key steps:
### Step 1: Inference Schema
A large language model (LLM) analyzes your documents and suggests the best JSON schema for them, regardless of the document type. This schema acts as the “official” structure for all files in the batch.
### Step 2: Invoice Data Capture
A specialized LLM maps the extracted fields strictly to the schema. For each uploaded document, it returns the data in a structured format, following the same structure every time.
### Step 3: Generate CSV
Once all documents are structured in JSON, another specialized LLM uses tools like Pandas to design CSV tables that clearly present the extracted data.
What I’d love to know is: **what do you think about this approach?** All feedback is welcome. Do you see the potential for this AI agent to revolutionize data extraction and processing?
Imagine the possibilities: medical professionals could easily analyze patient data, businesses could streamline their invoicing processes, and researchers could quickly process large datasets. The applications are endless.
Let me know your thoughts, and help shape the future of data extraction!