Mihup has entered into a collaboration with Qualcomm Technologies to co-develop and commercialise multilingual, enterprise-grade Voice AI solutions tailored specifically for the Banking, Financial Services, and Insurance (BFSI) sector. The initiative focuses on enabling advanced voice intelligence capabilities to operate directly on on-device AI platforms, reducing dependence on cloud infrastructure while strengthening privacy, performance, and scalability.
The partnership addresses several long-standing challenges faced by BFSI organisations as they accelerate digital transformation. Cloud-heavy Voice AI implementations often struggle with latency, bandwidth constraints, infrastructure expenditure, and data security concerns. By shifting AI workloads to devices powered by Qualcomm’s AI processing technologies, the two companies aim to deliver lower response times, stronger data governance, and enhanced privacy safeguards—particularly critical for highly regulated industries.
Under this collaboration, Mihup’s Voice AI contact centre platform will leverage a hybrid architecture. Core, high-frequency processes such as speech-to-text conversion and real-time agent assistance will be executed locally on Qualcomm’s Neural Processing Units (NPUs). More complex or scalable functions will continue to utilise cloud resources where required. This blended approach is designed to optimise performance while significantly lowering operational overheads and reducing reliance on continuous cloud connectivity.
Based on Mihup’s internal assessment, moving compute-intensive speech workloads to on-device processing can cut total cost of ownership by up to 78 percent, depending on deployment scale and usage patterns. The model is also expected to enable quicker response cycles, real-time conversational intelligence, and improved customer engagement—particularly relevant in linguistically diverse environments such as India.
The jointly developed solution is engineered to handle multilingual customer interactions across service, sales, and collections workflows, reflecting natural conversational patterns across regional languages. By ensuring that sensitive financial data is processed directly on the device, the architecture seeks to reinforce compliance standards and support data sovereignty requirements for financial institutions.
With commercial rollouts already underway in India, the collaboration is positioned as a proof of scale for on-device AI in enterprise Voice AI deployments. While the initial focus remains on India’s BFSI ecosystem, both companies intend to extend the offering to other emerging markets and regulated sectors globally, positioning on-device AI as a practical and secure alternative for large-scale enterprise adoption.
