From scanned documents to structured data
Turn messy business documents into structured, auditable data.
We build document intelligence systems that turn PDFs, scans, and complex business documents into validated, structured data — integrated directly into your existing workflows.
What we do
A focused set of document intelligence building blocks, wired directly into your existing workflow.
Classification & routing
Incoming documents are scanned or ingested, classified, and routed to the correct process or review queue.
AI document interpretation
OCR and document understanding recover structure and meaning from PDFs, scans, tables, forms, and inconsistent layouts.
Structured data extraction
The exact fields your systems need, extracted and validated against your domain rules — not a generic key-value dump.
Workflow integration
Processed data flows directly into the tools you already use — APIs, exports, queues, or existing systems.
Built with the right tools
Right model for the job
We combine scanning, OCR, vision models, language models, deterministic rules, and domain-specific logic instead of forcing every document through one model.
Deployment that fits the data
The architecture can be adapted to data sensitivity, infrastructure constraints, cost, volume, and deployment requirements.
Human-verifiable output
Important extracted data can be validated, audited, reviewed, and traced back to the source document.
Case study
- sections
- 16
- sections
- page documents
- 20+
- page documents
- languages
- 32
- languages
- audit trail
- Full
- audit trail
Problem
Safety Data Sheets are complex regulatory documents with overlapping standards, inconsistent formatting, multilingual content, and many domain-specific validation rules.
System
Chemplora ingests SDS documents — extracting text via OCR where needed — identifies relevant sections, extracts data into a strict domain model, applies domain validation and consistency checks, and supports human review.
Result
The resulting data is structured, validated, traceable, reusable, and suitable for downstream chemical and regulatory workflows.
Source PDF — Section 2
SAFETY DATA SHEET
2. Hazard identification
GHS Classification:
Flam. Liq. 2, Eye Irrit. 2
Signal word: Danger
H225, H319
Extracted & validated
{
"section": 2,
"hazardClass": [
"Flam. Liq. 2",
"Eye Irrit. 2"
],
"signalWord": "Danger",
"hStatements": ["H225", "H319"]
}
Capabilities
- Section-aware PDF processing
- OCR where required
- Multilingual extraction (32 languages)
- Translation memory
- Cross-section consistency checks
- Domain validation
- Full audit trail
Engineering, not marketing
Our founder writes openly about the systems, trade-offs, architecture, scanning workflows, OCR, document processing, and engineering decisions behind this work.
How it works
From a pile of PDFs to structured, audited data.
- 01
Send a sample
Share a representative set of PDFs, scans, or paper-document examples and the workflow around them.
- 02
We map the domain
We identify document structure, OCR requirements, required output, business rules, validation logic, and edge cases.
- 03
We build and verify the pipeline
We combine scanning or ingestion, OCR, extraction, models, deterministic rules, and validation into a system tested against real documents.
- 04
You get structured, audited data
The result is delivered through an API, export, or direct workflow integration, with traceability where required.
Have documents your current tools cannot reliably process?
Send us a representative sample. We'll tell you what can realistically be automated, how we would approach it, and where the hard parts are.