Indic languages present unique challenges for AI systems due to diverse scripts, morphology, and limited training data. Articles cover multilingual RAG with Bhashini, Indic language embedding strategies, and the engineering patterns for building AI that serves Hindi, Tamil, Bengali, and other Indian languages.
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An Indian banking deployment needs to handle Hindi, Marathi, Tamil, Bengali, and English in the same retrieval pipeline. Bhashini (the government's language stack) plus cross-lingual embeddings make it tractable.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.