Google Document AI sparks OCR debate

The real choice here is not “best OCR” but “how much document intelligence do you want the platform to handle for you.” For structured forms with human review in the loop, managed services usually win on time-to-result; open source wins on control and cost, but you pay for it in glue code.

• –Google Document AI Form Parser is a strong baseline for key-value pairs, checkboxes, and tables, but it is pre-trained and cannot be up-trained, so it fits stable form layouts better than drifting ones.
• –Azure AI Document Intelligence is the most flexible fit for template-heavy workflows because it supports custom models and composed models, which makes multiple form variants easier to manage.
• –AWS Textract is solid if you want AWS-native forms extraction and queries, but it still tends to push you toward more orchestration and post-processing when layouts vary.
• –PaddleOCR is attractive for a student project because it is open-source and configurable, but it is OCR-first, so you will need your own field mapping, confidence handling, and review UI logic.
• –Tesseract is fine as a benchmark baseline, but by itself it is not a full form-understanding stack.