Solution for partners
Document Intelligence
Upload documents, extract predefined schemas, and query structured data through RAG and intelligent assistants.
Overview
A smart document management system built so users can extract predefined schemas from files they upload. The system reads each file, converts it to text, maps content into schema fields, and saves both the source file and the extracted schema in a structured relational database. That data feeds RAG and intelligent systems that answer everyday questions and relational ones — for example what is the most expensive model, what is the longest warranty, or how many patients received a given medicine.
How it works
- 1
Partners define predefined schemas for their document types — the fields they need from each kind of file.
- 2
Users upload files against a schema; jobs are queued for asynchronous processing.
- 3
The system reads each file, converts it to text, and extracts raw text into the schema fields.
- 4
Extracted data is saved as exportable files and in a structured relational database, alongside the original upload.
- 5
Teams query the database for aggregates and comparisons, and connect the same data to search, APIs, and RAG or intelligent Q&A.
- 6
Queue-based workflows scale so large batches stay reliable at volume.
What we built
Predefined schemas per document type
Partners shape schemas to their workflows — invoices, contracts, medical forms, and more — so every upload maps to the same field layout.
Upload and async processing
Users upload PDFs and images against a schema; processing runs in the background with predictable throughput for operational volume.
Text extraction and field mapping
Files are converted to text and content is mapped into schema fields — structured output without manual re-keying.
Files plus relational storage
The platform keeps exportable extracts and a structured relational database so teams can audit, export, and analyse in one place.
RAG and intelligent Q&A
Structured data powers search, APIs, and assistants that answer both document questions and relational queries across records.
Questions
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