Capability
Intelligent Document Processing
The problem
A great deal of public-sector and enterprise work still arrives as PDFs, scans, faxed forms, email attachments, and correspondence, and is handled by a person who opens each one, decides what it is, types a few fields into another system, and files it. The cost is not one document; it is the same twenty minutes repeated several thousand times a year, with a backlog that grows whenever volume does and an error rate nobody measures.
Typical technologies
- Python
- OCR engines
- Document AI and layout models
- Vector databases
- Retrieval-augmented generation
- Hugging Face
- OpenAI and Anthropic APIs
- PostgreSQL
- Object storage
What we deliver
- Document ingestion from uploads, email attachments, scanners, file drops, and existing repositories
- OCR for scanned and photographed documents, including mixed-quality and multi-page material
- Document classification, so an item is identified before anything tries to read it
- Structured extraction of names, dates, identifiers, amounts, tables, and form fields
- Validation rules applied to extracted values before anything downstream accepts them
- Routing into the correct queue, workflow, or system of record
- Confidence scoring, with an exception queue for anything below the threshold
- Human-in-the-loop review screens showing the extracted value beside the page it came from
- Search across large document collections, including scanned material
- Retrieval-augmented question answering over a controlled collection, with citations to the source document
- API delivery of extracted data into an existing system rather than a second place to look
- Audit trails recording what was extracted, what was changed, and by whom
Examples of project types
These describe the kind of work we take on. They are illustrative scopes, not descriptions of completed client projects.
- An intake pipeline that accepts PDFs, scanned forms, and email attachments, identifies the document type, extracts the required fields, validates them, and routes the submission into the appropriate workflow
- A records-review system over case files, policies, reports, or contracts that lets authorized staff find relevant passages with links back to the source page
- A forms-processing service that extracts structured data, applies validation rules, flags ambiguous results for a reviewer, and posts approved records to an existing system through an API
- A backlog-reduction effort that indexes and makes searchable a document archive that currently exists only as scans
- A scoped proof of concept establishing whether extraction accuracy on a real sample clears the threshold the program needs before larger investment
Expected outcome
Staff stop retyping what a document already says, the backlog stops being a function of headcount, and every extracted value can be traced to the page it came from.
Built by us
Products that show this work
Questions
Intelligent Document Processing: common questions
What is intelligent document processing?
How do you keep extracted data accurate?
Can documents be processed without sending them to a public AI service?
Next step
A requirement for Intelligent Document Processing?
Or email contact@missionlayersystems.com or call (949) 501-1291.