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Humana
Entity recognition with vision-language models for fax and document digitization — extracting structured fields from unstructured clinical paperwork.
VLMEntity recognition
The Challenge
Faxed and scanned documents still carried critical member and clinical data that teams had to read and key by hand.
High-volume fax digitization meant inconsistent layouts, stamps, handwriting, and multi-page packets. Manual entity extraction slowed intake and introduced costly transcription errors before anything reached downstream systems.
Our Strategy
We deployed vision-language models to detect and extract entities directly from document images — not just OCR text dumps.
The pipeline handles fax and scan artifacts, maps extracted entities into structured schemas, and routes low-confidence fields for review so operations keep speed without sacrificing accuracy on regulated healthcare documents.
The Results
What changed after launch.
VLM
Entity recognition
Models read document images and pull the fields teams previously typed by hand.
Fax → data
Digitization path
Unstructured fax packets become structured records ready for downstream workflows.
Review loop
Confidence routing
Ambiguous extractions fields escalate cleanly instead of blocking the whole batch.
FAQ's
Answers To What You’re Wondering About.
Most projects go live within 2 to 4 weeks, depending on the complexity of your existing workflows and tools.
Setup typically takes a few weeks, though timelines vary based on how many systems need to be connected.
We provide ongoing support after launch, adjusting and refining the automation as your business needs evolve over time.
Yes, we’ve built automation for e-commerce, marketing, food and beverage, and software businesses across many different niches.
Pricing depends on project scope and complexity, and we always share clear, upfront estimates before any work begins.
We build flexible systems designed to adapt, and we’re available to update automation as your tools or needs evolve.