Integrating Didit's OCR API with Python for Document Data Extraction
Blog post from Didit
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Review evidence: 3,056 posts in March 2026; 671 shared March 14, 2026; preceding six-month median 13.5. Reviewed August 9, 2026.
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Didit’s OCR-powered ID Verification API is presented as a developer-focused Python integration for extracting and validating structured data from passports, identity cards, and driver’s licenses. The API accepts common image and document formats, authenticates requests with an API key, and supports configurable controls such as document liveness checks and minimum-age requirements to address fraud prevention and compliance needs. Its JSON verification reports include approval status, personal and document details, addresses, document media, authenticity information, and image-quality metrics such as focus, brightness, and resolution. Additional endpoints provide full session results, including liveness and face-match outcomes, and generate compliance-ready PDF audit reports. Didit positions its modular AI-native platform as scalable and secure, offering optional services including liveness detection, facial matching, and proof-of-address verification, alongside sandbox access, public documentation, free core KYC, no setup fees, and pay-per-successful-check pricing.
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