For technical readers: SamvadaAI is a retrieval-augmented dialogue system over a curated Indic corpus. The aim is source-grounded conversation—not freestanding generation that merely sounds wise.
Corpus digitization
Granthas are prepared as structured source material—text, tradition, and reference metadata—so a verse remains attached to its home rather than floating as a slogan.
Dense semantic embeddings
Passages are encoded into vector representations that capture meaning beyond exact keyword match, so a living question can find related shlokas even when wording differs.
Multi-path retrieval & reranking
Several retrieval routes surface candidates; a reranker then prefers passages that fit the question’s intent, language, and corpus focus before synthesis begins.
Grounded RAG synthesis
The model answers with retrieved source material injected into context. It is asked to stay with what the passages support—and to leave room for reflection rather than decree.
Citation traceability
Responses carry grantha and shloka (or chapter) references so you can open the primary text. A citation is a trail, not an oracle seal.
Indic language pipeline
Inquiry and answer move across major Indian languages—text and voice—so mother-tongue seekers are not gated behind English or Sanskrit fluency alone.
The loop remains human: you bring the question; the system retrieves and cites; you reflect with teachers, practice, and the text. Technology is the bridge. It is never the source of wisdom.
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