
AI/MLFeatured
Vyapar-Gyan
AI Marketplace with WhatsApp Commerce & Voice-First Shopping
The problem
India's next billion commerce users don't use web dashboards — they speak eight languages, live inside WhatsApp, and send voice notes, not typed SKUs.
My approach
Voice-first WhatsApp commerce: Gemini transcribes and classifies voice notes, routes intents to 65+ Lambdas across 12 domains, and AWS Polly responds in the customer's dialect.
What I built
Omnichannel commerce for Indian retailers. Customers shop via WhatsApp or web chat in 8 Indian languages using voice notes. Gemini 2.0 transcribes voice, extracts product intents, routes to seller. Features Khata book OCR, Razorpay Route splits, and Bedrock-powered dead-stock detection.
How it works
Full-stack serverless AWS architecture with 65+ Lambda handlers across 12 domains. Voice-first shopping in Hindi/English/Tamil/Telugu/Marathi/Bengali/Gujarati/Kannada. AWS Polly neural TTS for voice responses via WhatsApp. Proactive AI insights with severity scoring.
What I'd do differently
Voice-first isn't a novelty — it collapses a typing funnel that was quietly blocking non-English users entirely.
Good questions to ask
3 questions an interviewer could ask about Vyapar-Gyan
Why did you focus on voice notes instead of typed SKUs for India's next billion commerce users?
Based on:
India's next billion commerce users don't use web dashboards — they speak eight languages, live inside WhatsApp, and send voice notes, not typed SKUs.
How did you design the voice-first approach to address non-English users?
Based on:
Voice-first isn't a novelty — it collapses a typing funnel that was quietly blocking non-English users entirely.
How did you implement AWS Polly in the workflow?
Based on:
AWS Polly responds in the customer's dialect.
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At a glance
- Technologies
- 8
- Language
- TypeScript
- Updated
- Apr 2026
- AWS Lambda
- DynamoDB
- Twilio
- Razorpay
- Bedrock
- Gemini 2.0
- Next.js 14
- CDK
- #marketplace
- #whatsapp-commerce
- #voice-ai
- #serverless


