The ongoing AI Impact Summit 2026 has brought together global technology leaders, policymakers, startups, and AI innovators to discuss the future of artificial intelligence. As part of the five-day event, the AI Impact Expo was inaugurated by Narendra Modi on February 16, providing a platform for companies worldwide to showcase emerging AI products and solutions.
On the sidelines of the summit’s second day, Indian AI firm Mihup.ai announced a collaboration with US-based chipmaker Qualcomm to build on-device AI solutions tailored for the Banking, Financial Services, and Insurance (BFSI) sector. The companies claim the solution will enhance operational efficiency while improving data security.
In a LinkedIn post on Tuesday, the Indian AI firm announced that Mihup.ai is collaborating with US-based tech giant Qualcomm for the launch of the company's “first-of-its-kind” Edge Voice Intelligence stack, allowing Voice AI to process commands on-device. The AI firm highlighted that the AI-powered solution has been designed “specifically” for the Qualcomm Hexagon NPU.
By leveraging on-device processing, the stack aims to reduce latency and strengthen privacy by avoiding dependency on cloud-based infrastructure.
Mihup.ai claims that its tool “ensures that conversations get processed” only on-device, eliminating the need for the data to be transmitted to the cloud servers for processing.
The system utilises:
Native AI-backed Automatic Speech Recognition (ASR) technology
A Small Language Model (SLM)
The on-device voice intelligence stack has been optimised for more than 12 regional languages of India, along with code-mixed speech, addressing India’s multilingual and diverse user base.
This localisation is particularly significant for financial institutions operating in Tier 2 and Tier 3 cities where vernacular language support is critical.
Mihup.ai claims that the on-device solution is 80 percent more cost-efficient than “GPU-heavy cloud AI” tools.
Beyond cost advantages, the system is capable of:
Real-time violation detection
Coaching during live calls
Context-aware responses
Emotion recognition
These features are particularly relevant in the BFSI sector, where compliance monitoring and customer experience management are key operational priorities.
The Indian tech firm's Voice AI is designed to cater to the Banking, Financial Services, and Insurance (BFSI) sector, which involves numerous conversations between customers, potential customers, sales representatives, and customer care executives.
In an October 2025 blog post, the company claimed that Mihup.ai's Voice AI “improves” customer service in the BFSI sector.
According to the company:
The system detects urgency in a caller’s voice.
When urgency is identified, customers are routed directly to a representative instead of navigating additional IVR menus.
The tool retrieves account-specific customer data to offer personalised assistance.
It understands conversational context and avoids generic scripted responses.
Additionally, Mihup.ai says that its Voice AI tool can identify a customer's emotions through speech patterns. If the system recognises distress, it redirects the call to a human representative while handling simpler queries independently.
As AI adoption accelerates globally, financial institutions are increasingly prioritising:
Data sovereignty
Lower latency
Reduced cloud costs
Enhanced compliance
On-device AI solutions address many of these concerns by processing data locally, minimising transmission risks, and offering faster response times.
With regulatory scrutiny rising in financial services, privacy-focused AI deployments are becoming strategically important.
Conclusion
The collaboration between Mihup.ai and Qualcomm at the AI Impact Summit 2026 highlights India’s growing role in edge AI innovation. By developing a “first-of-its-kind” on-device Edge Voice Intelligence stack optimised for Qualcomm’s Hexagon NPU, the partnership aims to transform how BFSI institutions manage customer interactions.
With support for over 12 Indian languages, 80 percent cost efficiency compared to “GPU-heavy cloud AI” tools, and real-time compliance monitoring, the solution positions itself as a scalable and privacy-centric AI alternative for India’s financial sector.