The Security Risk of Public Cloud OCR
Handling sensitive financial records, medical documents, and enterprise agreements requires an uncompromising security posture. Modern organizations cannot simply send unencrypted customer records or trade secrets to public third-party APIs.
Meteor Document Processing was designed to execute either in private enterprise clouds or completely local, air-gapped environments. We utilize localized vision-language models combined with spatial bounding-box geometry to extract nested tables, line items, and signatures.
Deterministic Mathematical Reconciliation
Raw optical character recognition is inherently probabilistic. To achieve enterprise viability, probabilistic text extraction must be paired with deterministic mathematical validation rules.
Every extracted invoice or ledger record is automatically tested: line-item unit quantities multiplied by unit prices must sum exactly to the subtotal, taxes must reconcile against municipal tables, and signature certificates are verified against standard cryptographic hashes.