Evaluating Google Document AI for PDF Parsing - Table Extraction

The RD-TableBench evaluation assessed Google Document AI's table extraction capabilities, revealing a 64.6% average precision score, which is significantly lower than competitors like Reducto at 90.2% accuracy. Despite Google's strengths in multilingual OCR and strong AI/ML presence, Document AI struggles with complex table layouts, merged cells, and consistent recognition of table boundaries, leading to word drops and errors that compromise data integrity. Its performance is notably weaker than major providers like Azure and AWS, and even lags behind newer vision language models such as GPT-4o. The evaluation highlights significant limitations in Google's approach, with outdated methods and structural parsing issues making it less effective for enterprise-grade document processing. Consequently, organizations dealing with complex tables or large volumes face potential operational risks and could benefit from more advanced solutions that ensure higher accuracy and reliability.

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