Case Study
Xtracta
Overview
An AI-powered PDF data extraction platform with template management, AI integration (DeepSeek, Gemini), subscription management, and comprehensive API access.
Business Challenge
Businesses receive data locked inside PDFs — invoices, forms, statements — and staff manually re-key it into systems, slowly and with errors.
Why It Was Built
Built to turn PDFs into structured data automatically using AI extraction, so documents flow into systems without manual re-typing.
Target Users
Operations teams, accountants, and data-entry-heavy businesses processing PDF documents at volume.
Architecture
Laravel 12 pipeline: upload → text/table extraction → AI parsing (DeepSeek + Gemini) → validated structured output; queued processing for large batches; confidence scoring flags low-quality extractions for review.
Deployment
Laravel app on VPS with MySQL and dedicated queue workers for AI extraction jobs.
Scalability
Queue-based extraction scales to bulk document batches; AI provider abstraction allows swapping models.
Challenges
- Manual data extraction
- Time-consuming processing
- No AI integration
- Limited scalability
Solutions
- AI-powered extraction
- Template management
- Batch processing
- API access
Summary
AI-powered PDF data extraction using DeepSeek and Gemini — documents to structured data. Live at xtracta.in.
Technologies Used
Third-Party Integrations
- DeepSeek AI
- Google Gemini AI
- PDF parsing pipeline
- Queue workers
- Structured JSON/CSV export
Results & Metrics
Automated extraction
Reduced manual effort
Scalable processing
API integration
PDFs that took an afternoon to process now finish in minutes — with better accuracy.
Project Timeline
Phase 1: Core platform foundation
Phase 2: Template management
Phase 3: AI integration
Phase 4: Batch processing
Phase 5: Subscription system
Phase 6: API development
Phase 7: Export features
Try It Live
Experience the product in action
Measurable Outcomes
Document-to-data time reduced from minutes-per-page to seconds-per-document with AI-verified accuracy.
Designed & developed by Ankush Gautam
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