Document Intelligence at 50,000-PDF Scale
A document ingestion and search platform that makes roughly 50,000 PDFs searchable — with every answer traceable back to its source page.
- Client
- B2B data platform (confidential)
- Duration
- Ongoing
- Team
- ElegantMind engineering team
- Industry
- B2B SaaS
What had to change
Tens of thousands of vendor PDFs in inconsistent formats made the client’s most valuable data effectively unsearchable — and answers without source citations could not be trusted
Architecture and delivery
A normalization and validation pipeline feeding a search platform where every result carries citations back to the exact source pages
The client’s core asset was a large corpus of vendor PDFs — around 50,000 documents in inconsistent formats that were effectively unsearchable. We built the ingestion pipeline (multi-vendor normalization, validation, and a quarantine path for malformed documents, with a pytest-backed test suite), and a search experience where results cite the exact source pages they came from. Traceability was a design requirement, not an afterthought.
A document corpus that was effectively dark became a queryable, evidence-backed asset
~50,000 PDFs ingested, normalized, and made searchable
Validation pipeline with quarantine for malformed documents
Every search result traceable to its source pages
Let's build something that matters.
Tell us what you have in mind. We'll talk through the possibilities, the practicalities, and the best place to start.