Enterprise communication will never sound the same once machines are able to speak as naturally as humans.

By creating speech models that are smaller, faster, and surprisingly human, Smallest.ai, a deep-tech startup, is redefining what voice AI can accomplish.  The company has transformed its audacious idea into production-ready technology in just one year after its founding, establishing new standards for the worldwide speech AI market.

Smallest.ai, which was founded by Sudarshan Kamath and Akshat Mandloi, has raised $8 million in seed funding headed by Sierra Ventures after 3one4 Capital led a pre-seed round.  The business is developing one of the quickest and smallest speech models in the world to enable realistic, real-time voices for businesses in a variety of sectors.

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By developing voice AI from the ground up, Smallest.ai is making it more expressive, quicker, and smaller than traditional voice systems, which frequently lag or sound artificial.  The company’s inventions are establishing new benchmarks for realism, cost-efficiency, and latency, demonstrating that accuracy, not size, is what AI is all about in the future.

Businesses spend more than $400 billion a year on human resources and contact centers worldwide, yet many technologies are unable to adequately capture complexity or size.  This problem is addressed by Smallest.ai, a full-stack voice automation platform that combines language comprehension, synthesis, and speech recognition into a single, production-ready solution.

Smallest.ai has advanced significantly in terms of technology in just a single year:

• Decreased the lag between text and speech from about two seconds to just 100 milliseconds
• Powered millions of business calls each month after scaling from concept to production.
• Improved naturalness of voice, including inflection, pauses, and emotion
• TTS expenses were scaled down from $0.20 to $0.01 each minute.

The company’s culture is defined by a combination of scientific rigor, engineering depth, and customer-driven iteration, which is reflected in this quick progress.

Smallest.ai’s main text-to-speech model, Lightning, is at the core of their platform. It uses less than 1 GB of VRAM and produces 10 seconds of realistic speech in under 100 milliseconds.  It is accompanied by Electron, a little language model that outperforms GPT mini in terms of conversational quality and latency.

When combined, these models enable real-time, human-like communication for industries such as healthcare, retail, and finance while upholding enterprise-level compliance with GDPR, SOC 2 Type II, HIPAA, and ISO 27001 standards.

One of the few businesses in the world that can control the complete conversational loop at production scale is Smallest.ai, which has built a comprehensive conversational stack from waveform to answer.  Its versions guarantee sub-100 ms response time and exceptional audio fidelity at a cost four times lower than their industry counterparts.

The company’s low-power, privacy-first design demonstrates that smaller is actually smarter and follows the emerging trend in AI toward modular, effective, and edge-deployable architectures.

With its headquarters in India, Smallest.ai is a prime example of a new wave of deep-tech businesses that combine scalable enterprise execution with an aspiration for global research.  Its design supports 3one4 Capital’s overarching applied AI thesis, which is the transition from scientific discoveries to production-grade infrastructure that revolutionizes business processes.

Smallest.ai is redefining what it means for robots to sound human as the world moves away from chat-based interfaces and toward voice-driven ones. It is also creating a new standard for how technology speaks, listens, and comprehends.