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Intelligent Document Processing
Get clean, structured data out of contracts, forms, invoices, and filings, with confidence scores and human review where it matters.
The problem
Critical information is trapped in PDFs and scans, re-keyed by hand, and slow to act on.
The outcome
A pipeline that reads documents at volume, structures the fields you need, and flags low-confidence cases for a person.
What we build
- Landing buckets to event-triggered processors: upload, then automatic ingest
- Gemini and Document AI extraction into structured BigQuery metadata
- Classification and field extraction tuned to your document types
- Confidence scoring with human-in-the-loop review queues
- Indexing into search and operator guides for upload → extract → review
- Throughput and accuracy monitoring over time
Technical foundation
Document AIGemini on Vertex AIEventarcCloud RunBigQuery
Typical deliverables
- Extraction pipeline for your document set
- Review interface and exception handling
- Accuracy and throughput baseline
- Integration into systems of record
Example use cases
- Contracts and SOW intake and obligation tracking
- Invoice and AP processing with validation
- Forms, applications, and compliance filings at scale
Governance & security
Sensitive fields are handled with access controls and retention rules. Human review is the default for anything below a confidence threshold you set.
Start here
Scope a Intelligent Document Processing engagement.
Tell us what you are trying to ground in AI. We will tell you the honest path to production.