CASE STUDY · DOCUMENT INTELLIGENCE
Turning large volumes of documents into answers.
Business teams collect more documents than they can read, sort and search by hand. This platform uses OCR and AI to process, organise and query documents in one workflow.
PROJECT OVERVIEW
- INDUSTRY
- B2B SaaS
- PROJECT TYPE
- Document workflow platform
- CAPABILITIES
- OCR, RAG, Document Classification, Information Extraction
01 · THE CHALLENGE
Plenty of documents, not enough answers.
Teams collect large volumes of business documentation: contracts, forms, reports, checklists and correspondence.
Finding the right answer means opening and reading files one by one. Understanding what each document contains and filing it in the right place takes time, and the more documents arrive, the more of the team's day goes to handling them.
The goal was a single workflow where documents could be processed, organised and queried without the manual sorting.
02 · THE SOLUTION
One workflow, from upload to answer.
Documents move through a series of AI steps, with routing decisions based on what each document actually contains.
- 01
Upload
Teams upload business documents into the platform.
- 02
OCR processing
Each document is read with OCR so its text becomes searchable and usable.
- 03
Classification and naming
Documents are classified and given clear names automatically.
- 04
Folder routing
Each document is routed to the right folder based on its content.
- 05
Extraction and search
Key information is extracted, and documents can be searched and analysed.
- 06
Ask and collaborate
A chatbot answers questions from the uploaded documents, alongside real-time assistance and team chat.
03 · KEY CAPABILITIES
What the platform does.
OCR-based document processing
Turns scanned and digital documents into text the system can work with.
Document-grounded chatbot
Answers questions using the content of the uploaded documents.
Information extraction
Pulls key details out of documents instead of copying them by hand.
Automatic classification and naming
Identifies what each document is and names it consistently.
Automatic folder routing
Files each document in the right place based on what it contains.
Search and analysis
Makes the full document set searchable and easier to analyse.
Real-time assistance and team chat
Helps people work on documents together as they go.
04 · TECHNOLOGY
Built with
- AI
- Model APIs, OCR
- Knowledge
- Custom knowledge layer (RAG)
- Extraction
- Rule-based extraction
- Data
- Custom data layer
05 · OUTCOME
A working document workflow, end to end.
The project delivered a SaaS workflow where teams upload, process, query, analyse and organise documents in one place.
It shows how OCR, classification and a document-grounded assistant can replace manual sorting and searching with a single, consistent process.
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