CallMissed Blog
Insights on AI communication, voice agents, WhatsApp automation, and the future of customer engagement.
5 min readBuilding a Hindi Chatbot for Indian SMEs in 2026
India has over 63 million SMEs, and the vast majority operate in regional languages. Hindi alone is spoken by over 500 million people. Yet most AI chatbots are built for English-first users. In 2026, new models, better datasets, and cheaper deployment mean a Hindi chatbot for Indian SMEs is a deploy…
5 min readAI in Indian Agriculture: Use Cases and Deployment Models in 2026
Indian agriculture employs over 40% of the workforce and contributes roughly 18% of GDP. Yet productivity lags behind global averages. In 2026, AI is addressing crop disease detection, yield prediction, supply chain optimization, and farmer advisory services. Key Use Cases - Crop Disease Detection: …
Sarvam Saaras V3: Why India's STT Beats Global Models
For most of the last decade, building voice products in Indian languages meant accepting that STT accuracy would be 30–50% worse than what English-language users took for granted. Code-mixing, accent variation, and 22 official languages with very different scripts conspired against the global ASR ve…
Sarvam Bulbul: TTS for Indian Voices and Code-Mixing
The hardest test of an Indian-language TTS model is not pronunciation — it's a sentence like "Aap apne SBI account ki KYC pending hai, please complete it before 25 तारीख." A name, an acronym, code-switched English, a Hindi date marker, and the whole thing has to sound like a real person reading a re…
AI in Indian BFSI: The Vernacular Voice Opportunity
India's financial services market has a structural problem English-trained AI cannot solve: the next 500 million banking and insurance customers do not speak English as their primary language. They speak Hindi, Tamil, Telugu, Bengali, Marathi, Gujarati, Kannada, and a dozen others. Voice — not chat …