Extract Accurate Green Card OCR Data in Seconds

Our layout-aware field capture reads the card as a document, not just a string of characters, so it keeps fields like name, USCIS number, category, and dates in the correct order. It’s designed to handle common real-world issues like tilted mobile photos, partial crops, and uneven lighting with fewer mis-assignments.

You receive a clean, structured JSON payload with consistent keys so the results drop directly into KYC, onboarding, or case management workflows. This reduces brittle post-processing and makes it straightforward to validate required fields such as document number and expiration date.

Yes—each extracted field can include verifiable metadata and citations (location details) so reviewers can trace values back to the exact spot on the image. That speeds up QA, supports dispute resolution, and improves auditability without re-checking the entire document.

We run automatic correction loops that validate and self-correct frequent failure modes, such as O/0 or I/1 swaps, dropped characters, and broken line segments. The result is higher straight-through processing rates, especially on low-resolution or shadowed captures.

Yes—the parser is built to capture key Green Card fields as discrete, structured values rather than leaving you to infer them from raw text. Layout-awareness helps ensure each field is mapped to the right label even when the scan is imperfect.

Because the output is standardized JSON, most teams can connect it to existing forms, validators, and case tools with minimal transformation. Start with the fields you need today and expand coverage as your workflow evolves, without rewriting fragile parsing rules.