Amid growing momentum around artificial intelligence innovation, the AI Impact Summit 2026 is bringing together industry leaders, technologists, and global companies focused on next-generation technologies. The 5-day event also features an AI Impact Expo, inaugurated by Prime Minister Narendra Modi on February 16, where technology firms are showcasing new solutions.
During the second day of the summit, Indian AI company Mihup.ai announced a collaboration with US-based chipmaker Qualcomm to build on-device AI solutions for the financial services sector, aimed at improving operational efficiency.
In a LinkedIn post shared on Tuesday, the company revealed plans to launch its “first-of-its-kind” Edge Voice Intelligence stack. The solution enables Voice AI to process commands directly on-device and has been designed “specifically” for the Qualcomm Hexagon NPU.
The company stated that its tool “ensures that conversations get processed” entirely on-device, removing the need to send sensitive data to cloud servers. The system uses AI-powered Automatic Speech Recognition (ASR) technology to convert speech into text, along with a Small Language Model (SLM). The voice intelligence stack has been optimised for more than 12 Indian regional languages and supports code-mixed speech.
According to Mihup.ai, the on-device solution is 80 percent more cost-efficient compared to “GPU-heavy cloud AI” tools. It is also capable of real-time violation detection and coaching during customer calls. The Voice AI platform is designed specifically for the Banking, Financial Services, and Insurance (BFSI) sector, where customer interactions play a critical role.
In an October 2025 blog post, the company noted that its Voice AI “improves” customer service experiences. The system can detect urgency in conversations and route customers directly to human representatives instead of navigating multiple IVR menus.
Additionally, the AI tool can retrieve account-specific data to provide personalised assistance. It understands conversational context and delivers responses accordingly rather than offering generic replies. The system can also analyse customer emotions through speech. If distress is detected, calls are redirected to human agents, while simpler queries are handled automatically.
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