Designing Production-Scale OCR for India: Multilingual and Domain-Specific Systems

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• Fine-tuning an existing OCR model for target languages achieves better accuracy-latency trade-offs than training a vision-language model end-to-end for multilingual OCR.result 85%
• Chitrapathak-2 achieves 3-6x speedup over its predecessor while achieving state-of-the-art performance in Telugu OCR.result 90%
• Parichay OCR model series achieves 89.8% Exact Match score for extracting structured key fields from 9 Indian government documents.result 90%
• The system may not easily adapt to languages or scripts not initially included in training.limitation 80%
• The OCR system relies on substantial initial data for training.limitation 85%
• The research addresses a significant gap in OCR capability for India's diverse and complex document landscape.market 75%
• The target market includes Indian enterprises and government sectors requiring automated document digitization due to linguistic diversity.market 80%
• Chitrapathak-2 achieves second best performance in languages other than Telugu.result 85%

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