Privacy-First OCR Pipeline

The Challenge

A partner in a compliance-heavy industry needed to extract structured data from physical ID cards and documents. However, sending sensitive PII (Personally Identifiable Information) to cloud-based LLM APIs posed unacceptable privacy risks.

The Solution

I built a Hybrid OCR Pipeline designed to run entirely on the edge:

• Vision Layer: Utilized robust open-source OCR engines for text detection and extraction.
• Reasoning Layer: Deployed quantized local LLMs (via Ollama) to clean, parse, and structure the messy OCR output into valid JSON.
• Orchestration: Layered a custom agent to provide grounded reasoning about the document content (e.g., verifying coverage dates) without data egress.

The Impact

Achieved 100% data sovereignty. No raw images or text leave the local environment during the extraction process, satisfying strict regulatory requirements while automating manual data entry.