Meesho Launches “Vaani – Your Meesho Dost”, India’s first Gen-AI powered Conversational Voice Shopping Assistant

Meesho Launches “Vaani - Your Meesho Dost”, India’s first Gen-AI powered Conversational Voice Shopping Assistant

Bengaluru, Mar 24: Meesho today announced the launch of “Vaani – Your Meesho Dost”, India’s first Gen-AI powered conversational voice shopping assistant purpose built for the next 500 million users who inherently shop offline.

In offline settings, shopping has always been conversational. People describe what they need, ask questions, compare options and seek reassurance before making a purchase. However, this behaviour has not translated easily to digital commerce. For many, especially across tier 2+ markets, navigating apps through typing, filters and structured search can feel unintuitive.

“Vaani – Your Meesho Dost” is designed to bridge this gap by bringing conversational shopping into the digital experience. Users can speak in their own words, ask follow-up questions and refine their choices through a natural, ongoing conversation. With this launch, Meesho is taking steps towards its broader vision of conversational commerce, reimagining how users interact with e-commerce through more natural, voice-led experiences.

The assistant is designed to support users across the entire shopping journey, from discovery to purchase. It understands user intent by asking relevant follow-up questions, helps surface the most relevant products without extensive browsing, and addresses decision-making barriers through contextual information like reviews and product details. It also guides users through key steps such as selecting payment methods and confirming delivery details, reducing friction across the purchase process. Built for scale, the system leverages on-device processing to deliver a faster, more efficient experience while optimising costs.

The assistant is powered by a robust AI architecture designed for real-world usage at scale. It leverages edge computing for speech understanding and synthesis to ensure low latency and cost efficiency, while a multi-agent framework enables it to handle complex, multi-step shopping interactions reliably.

The system is further strengthened by fine-tuned models trained on regional language nuances, allowing for more accurate and context-aware responses. With multi-modal capabilities, the assistant can understand both what users say and what they see on the screen, enabling a more seamless and context-rich shopping experience

Sanjeev Kumar, Co-Founder and Chief Technology Officer, Meesho Limited, said, “At Meesho, AI has always been at the core of how we build for scale. With over 251 million annual transacting users, we have a deep understanding of how India shops, and that allows us to anticipate and solve for consumer needs in ways that very few platforms can.” 

“Over the years, we have embedded AI and ML across every part of our marketplace, from discovery and pricing to logistics, trust and seller growth. Vaani is a natural extension of this journey. It brings together conversational AI with Meesho’s commerce intelligence to support users from discovery to purchase.

The assistant understands user intent, asks follow-up questions, surfaces relevant products, and guides users through key steps in the purchase journey, making the experience more intuitive. Built for real-world usage at scale, it delivers fast, reliable, and context-aware interactions.

We believe this is a meaningful step towards making e-commerce more accessible and more human, and towards shaping a future where technology adapts to people, not the other way around,” he added.

Early adoption shows strong user confidence, with 79% saying voice simplifies shopping, 94% finding it intuitive, and 62% already trusting it for transactions.

Within the first month of launch, over 1.5 million users have interacted with the assistant. Engagement is repeat-led, with users returning frequently and engaging in multiple conversations over short periods, indicating early habit formation.

This is translating into measurable impact, with users who engage with the assistant seeing a 22% higher conversion rate, moving more efficiently from discovery to purchase, and showing lower returns and cancellations.

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