Gupshup’s AI Rebuild: Can It Stay Ahead Of The Platforms It Runs On?

by · Inc42

SUMMARY

  • Gupshup is shifting from messaging infrastructure to AI-powered customer engagement, with AI offerings already contributing 25–30% of its global revenue.
  • As messaging infrastructure becomes more competitive, Gupshup is betting that its 20-year enterprise relationships and existing customer base can give it an edge in the race for enterprise AI.
  • With a potential 12–24 month IPO window, investors will ultimately judge whether its AI pivot can drive higher revenue, margins and a durable moat.
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For a company that started out sending SMSes, Gupshup has spent nearly two decades learning one thing: how businesses talk to their customers.

That experience is now becoming the foundation for its next bet: conversational AI.

Gupshup is no longer positioning itself simply as a messaging infrastructure company. Its product stack is expanding from SMS and WhatsApp to voice AI, AI agents, campaign orchestration and tools that allow enterprises to connect multiple AI models with customer-engagement channels.

The shift is already showing up in the business. At the global level, CEO and cofounder Beerud Sheth said for FY26, Gupshup is roughly $350 Mn business and profitable. 

But that is not the real story here given that global revenue in FY23 was around $300 Mn. More importantly, Sheth said 25% of the revenue today now comes from AI-related offerings. And this transition also resulted in some workforce reduction over FY26, but the CEO believes Gupshup is different from a conventional startup launching an AI product because it has seen how communication and messaging has evolved.

Today, Gupshup is effectively trying to AI-ify an existing enterprise customer base, using the infrastructure, relationships and transaction volumes accumulated over years as its competitive moat.

From Messaging APIs To AI-Powered Conversations

Gupshup’s evolution has broadly tracked the evolution of customer engagement.

The company started with SMS and basic messaging in 2004. WhatsApp brought richer, two-way conversations, while RCS and other channels expanded the ways businesses could interact with customers. Gupshup now sees AI-powered conversations across text and voice as the next stage, having entered the segment in February 2025. 

“We’ve been doing this business for 15–20 years,” Sheth said in an interaction with Inc42. The company’s focus, he said, has been helping businesses engage customers through mobile messaging and voice, with newer interfaces potentially emerging over time.

The important distinction is that Gupshup does not see voice AI as a standalone channel.

Its recently launched voice AI offering is a self-serve platform for deploying AI agents that handle customer calls. The company says these agents can resolve inbound support calls, qualify leads and automate operational calls such as scheduling, verification and payment reminders.

The platform starts at $0.035 (₹3.50) per minute, compared with industry pricing that can range from $0.05 to $1 per minute. Sheth expects the cost of voice AI to fall further as the underlying technology becomes more efficient. Gupshup is also experimenting with smaller, specialised models that can deliver faster and cheaper inference for specific use cases.

The platform is model-agnostic, with integrations including Deepgram, ElevenLabs and Cartesia. The company is also evaluating open-weight and Indian models.

Gupshup’s existing voice infrastructure is another part of the equation. The company acquired voice technology business Knowlarity in 2022 for $100 Mn, giving it an established voice stack. According to Sheth, Knowlarity’s infrastructure handles around 500 Mn calls a month.

Gupshup is now adding an AI layer to that infrastructure and integrating it with the broader platform.

Voice AI is only one part of that strategy. In April, the company introduced Super Agent, an orchestration layer designed to bring multiple customer-engagement functions into a single interface.

Businesses today have to manage messaging channels, campaigns, customer journeys, AI agents, CRM systems, payments, catalogues, human escalation and analytics, often across different platforms. Super Agent is designed to bring these workflows together through natural-language instructions.