ContextBuilder: From Unstructured Documents to Trusted Data
A claims document pipeline that turns PDFs, scans and images into structured, quality-checked claim data, with human review where it matters.
The Document Chaos Problem
Claims arrive as chaotic document bundles: blurry photos, multi-page PDFs, scanned forms. Extracting accurate data is slow, error-prone and expensive.
Purpose-Built Pipeline for Claims
ContextBuilder is a purpose-built pipeline for claims documents. It automatically ingests, classifies and extracts data, then applies quality gates to surface exceptions for human review.
The result: claim-ready "context packs" that downstream systems can trust.
5-Step Pipeline
From raw documents to structured data
Ingest
Transforms documents into machine-readable text and layout using advanced OCR and vision models.
Classify
Identifies document type and language to route correctly: loss notice, police report, invoice etc.
Extract
Pulls structured fields based on document type. Normalizes so same concept looks the same everywhere.
Quality Gates
Automated checks validate completeness and consistency. Pass / Warn / Fail scoring.
QA Console
Human-in-the-loop review workspace. Quickly confirm, correct and label documents.
All document processing is designed to meet enterprise security, privacy and regulatory requirements. Visit our Trust Center for more details.
What You Get: A Claim-Ready Context Pack
Clean structured dataset
Key fields extracted and normalized
Quality status
Pass/Warn/Fail per document and run
Evidence links
From each field back to originating document text
Human labels
Optional notes where review was performed
Performance Metrics
95%
Document Coverage
99%
Accuracy
96%
Evidence Rate
<1%
Document Classification Error Rate
Based on client data
Process a Sample of Your Documents
Securely share a sample of claim documents. We'll run them through ContextBuilder and show you the extraction quality, error analysis and time savings.
Book a Demo