Shunya Labs, known for building real-time AI systems focused on privacy and precision, has introduced Pingala V1, its most advanced speech recognition model to date. Developed on a modest $4 million budget, the system delivers high performance in speed, multilingual support, and word accuracy. Initially designed to improve transcription in mental health settings—where confusing words like “quetiapine” with “cutiepie” could lead to serious medical errors—the model is now being deployed across broader applications, including emergency response, defense operations, and enterprise call centers.
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What sets Pingala V1 apart is its real-time processing and ability to understand language and meaning with contextual awareness. It can follow complex conversations even as speakers switch dialects or accents mid-sentence. The model links spoken words to the right context, making it possible to connect symptoms to diagnoses or support calls to relevant service actions. It also retains details from earlier in a conversation to enable smooth and informed follow-up. With a response time of less than 250 milliseconds, Pingala V1 is built for environments where speed and precision are crucial.
Ritu Mehrotra, founder and CEO of Shunya Labs, stated, “While big AI companies that spend trillions of dollars still have trouble telling similar-sounding words apart, our team has created the most accurate speech recognition system in the world. We didn’t build it to win competitions. We built it because patients were dying while waiting for doctors’ notes to be accurately written down. Now, the model is ready to be used in hospitals, defense research labs, call centers, and anywhere else where people can’t afford to waste time.”
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Pingala V1 is engineered for real-world use. It supports over 200 languages and dialects and runs on standard CPUs—meaning it doesn’t require expensive GPUs or constant internet connectivity. This makes it easier and more affordable to deploy in sensitive locations where cloud access isn’t an option. The model achieved a word error rate of just 2.94 percent across eight speech recognition benchmarks, showing a 50 percent improvement over its nearest rival. It is available via API, Docker, and edge-ready versions, and is compliant with SOC 2 and HIPAA standards.
As demand grows for transparent, secure, and fast AI, Shunya Labs is offering a compelling alternative to black-box systems from larger tech players. By targeting sectors like healthcare, defense, and field services, the company is delivering specialized tools that bring clarity and reliability to real-time voice and language interactions.
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