Mihup and Qualcomm Partner to Deliver On-Device Voice AI for BFSI Sector

Mihup and Qualcomm Partnership Targets Enterprise Voice AI Transformation

Indian Voice AI company Mihup has joined forces with Qualcomm Technologies to develop enterprise-grade, on-device multilingual Voice AI solutions specifically designed for the Banking, Financial Services, and Insurance sector 1

1

2

2

. This collaboration marks a shift in how Voice AI operates in regulated industries, moving intelligence directly onto devices rather than relying on cloud infrastructure. The partnership addresses growing demands for AI-powered customer engagement while tackling persistent challenges that cloud-only Voice AI deployments face, including cost pressures, bandwidth constraints, latency issues, and concerns around sensitive customer data exposure.

The collaboration enables AI to run directly on devices, fundamentally changing the economics and security profile of voice-enabled customer service. According to Tapan Barman, CEO of Mihup, the partnership delivers an 80% cost reduction by eliminating recurring infrastructure expenses while providing total data sovereignty directly on the silicon 2

2

. By merging Qualcomm's NPU capabilities with Mihup's proprietary voice stack engineered for vernacular and on-device usage, the solution addresses India's linguistic diversity and cost-sensitive environment while maintaining applicability to other developing markets and regulated industries.

Secure Voice AI Solutions Address Critical BFSI Requirements

As BFSI organizations accelerate digital transformation, the need for secure Voice AI solutions has intensified. The Mihup and Qualcomm partnership specifically targets the governance of sensitive customer data, a critical concern for financial institutions handling confidential customer information 1

1

. On-device AI processing strengthens data privacy by keeping information local rather than transmitting it to cloud servers, addressing regulatory compliance requirements that financial services face globally. This approach delivers faster customer service while improving agent productivity through real-time, low-latency voice processing that doesn't depend on network connectivity or cloud availability.

The solution is designed to reduce latency and lower costs simultaneously, addressing two pain points that have limited Voice AI adoption in price-sensitive markets. Initial deployments in India will validate the on-device AI model at scale, testing its performance across the country's complex linguistic landscape 2

2

. The technology aims to enhance agent productivity by providing instant voice processing capabilities that work reliably even in environments with limited bandwidth or intermittent connectivity, common challenges in developing markets where BFSI institutions are expanding their digital footprint.

On-Device AI Shifts Voice Technology Economics

The move toward on-device multilingual Voice AI represents a fundamental architectural shift in how enterprises deploy conversational AI. Traditional cloud infrastructure models require continuous data transmission, creating ongoing operational expenses and potential security vulnerabilities. By processing voice interactions locally on devices, the Mihup-Qualcomm solution eliminates these recurring costs while delivering consistent performance regardless of network conditions. Tapan Barman emphasized that this transition moves Voice AI "from vision to production reality," providing frontline workers with technology that is secure, instant, and built to scale 2

2

.

This partnership positions both companies to capture growing demand in regulated industries beyond BFSI, where data sovereignty and compliance requirements make cloud-based solutions challenging to implement. The technology's focus on multilingual capabilities addresses real-world needs in diverse markets, where customer engagement often requires support for multiple regional languages. As financial institutions continue investing in AI-driven customer service, the ability to deploy Voice AI without compromising on security, cost, or performance could accelerate adoption across emerging markets where infrastructure limitations have previously constrained technology deployment.