PDF Analyser Documentation

Extract, classify, and structure data from financial PDFs using AI-powered document analysis.

Overview

The PDF Analyser automatically extracts data from financial PDF documents — bank statements, invoices, receipts, tax documents, and more. It uses advanced OCR and document AI to understand financial context, recognise table structures, and output structured data.

Supported Documents

Bank statements (any format)
Invoices and pro-forma invoices
Receipts and payment confirmations
Tax documents and assessments
Financial reports and summaries
Scanned paper documents (via OCR)

API Reference(Developers)

Upload a PDF document for AI-powered analysis. The engine extracts text, segments the content, generates section summaries, and combines them into a structured report with key findings, statistics, conclusions, and recommendations. Integrate and call the endpoint from your app and get structured analysis in the response.

You can create a developer account to get an api key fromhere.

POST https://server.gimele.com/api/v1/analyse-pdf

Upload a PDF file and receive a streaming AI-generated analysis report.

Headers

Authorization: Bearer <your-api-key>
Content-Type: multipart/form-data

Form Data Parameters

Parameter	Type	Required	Description
file	File	Yes	PDF file to analyse (max 50 MB)

curl -X POST https://server.gimele.com/api/v1/analyse-pdf \
  -H "Authorization: Bearer $GIMELE_API_KEY" \
  -F "file=@./financial-report.pdf"

Response

Returns a streaming text response (text/plain; charset=utf-8) containing the AI-generated analysis report. The report includes main topics, key findings, important statistics, conclusions, and recommendations.

Content-Type: text/plain; charset=utf-8
X-Cache: MISS (or HIT on subsequent requests)
---
# Analysis Report
## Main Topics
- Financial performance overview
- Revenue breakdown by segment
- Operating expense analysis
## Key Findings
- Total revenue grew 18% year-over-year to ₦2.4B
- Operating margin improved from 12% to 15%
- Debt-to-equity ratio decreased to 0.8
## Recommendations
- Expand into underpenetrated regions...
- Optimize supply chain costs...

Error Responses

400 Bad Request — No File

{
 "detail": "No file provided"
}

→ Fix: Attach a PDF file using the file form field with your request

400 Bad Request — No Text Extracted

{
 "detail": "Could not extract text from PDF"
}

→ Fix: Ensure the PDF contains selectable text (not scanned images only); use a PDF with embedded text or run OCR first