Qualcomm Ventures Backs ToneTag to Build Edge AI-Powered, Payment-Capable Devices from India

ToneTag, a deep-tech company pioneering sound-wave-based communication protocols, has secured a strategic investment from Qualcomm Ventures, the investment arm of semiconductor and telecommunications equipment company Qualcomm Incorporated. 

The funding will accelerate the development of edge AI and proximity-based payment capabilities across a wide range of connected devices.

At the centre of the collaboration is ToneTag’s ambition to build what could be among the world’s first Edge AI-powered, payment-capable modules—designed and engineered in India for global deployment. By combining high-performance on-device processing with real-time contextual awareness via its proximity protocol, ToneTag aims to turn everyday devices into intelligent, conversational, and payment-ready ecosystems.

Use cases span legacy payment infrastructure and modern consumer electronics—including smart TVs, smartphones, wearables such as smartwatches and smart glasses, and emerging IoT form factors. The architecture is particularly suited to high-volume environments like payments, identity verification and device-to-device exchanges.

“The real differentiation in computing is happening at the edge,” Kumar Abhishek, Founder and CEO, ToneTag, said. “With our proximity context protocol, we are laying the foundation for a new class of intelligent, payment-ready edge devices that can scale globally.”

Rama Bethmangalkar, Senior Director, Qualcomm Technologies and MD at Qualcomm Ventures India, mentioned, “ToneTag’s innovation combines powerful on-device AI with contextual intelligence, unlocking secure real-time payments across industries and devices.”

ToneTag’s payment protocol is already live across millions of touchpoints, processing over 25 million transactions daily—more than $3 billion in monthly transaction value. Its patented technology operates using existing device hardware, including speakers and microphones, enabling rapid, cost-effective adoption at scale.

Unlike many AI-led payment platforms, ToneTag is not using third-party AI models or centralised AI modules.

“What we are building is an Edge AI-powered payments capability where intelligence runs locally on the device, not in the cloud,” Abhishek told AIM.

The collaboration aims to enable a new generation of payment experiences in which everyday devices—from smartphones and smart TVs to wearables and emerging IoT form factors—become intelligent, payment-capable endpoints through local processing and contextual awareness.

“Our approach is not based on collecting large user datasets or training centralised models,” Abhishek added.

Instead, the company has designed its technology so that intelligence and context operate directly on the device, using real-time proximity and contextual signals. 

“ToneTag is not sourcing language datasets or training language models,” he mentioned. The system focuses on conversational payments and merchant–device interactions enabled by on-device contextual intelligence. This allows merchants to interact with payment devices in their preferred language, without relying on cloud-based language processing or large-scale data aggregation.

By shifting intelligence to the device itself, edge AI-powered payments enable faster user experiences through ultra-low-latency decision-making, while ensuring higher reliability even during network disruptions or backend outages. This on-device approach delivers stronger resilience in high-volume, real-world payment environments, where connectivity can be unpredictable, and significantly improves privacy and accessibility by reducing dependence on cloud-heavy architectures and centralised data processing.

Crucially, this model enables everyday devices—phones, wearables, smart TVs, and IoT endpoints—to function as secure, intelligent, payment-capable touchpoints, driven by contextual, on-device intelligence.