Smallest AI
Building AGI with small, efficient multi-modal models (<10B parameters) to make speaking to AI as natural and low-latency as speaking to a human.
At a Glance
- Enterprise Contact Centers
- Fintech
- Healthcare
- B2C AI Applications
- +1 more
AI Tools by Smallest AI
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Smallest AI
Efficient Multimodal AI Models Platform
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Latest News
Smallest.ai raises $8M seed to redefine enterprise Voice AI
Smallest.ai to use $8 million seed funding to train multimodal AI model 'Hydra'
Launch of Lightning V2: Ultra-low latency voice synthesis
Smallest.ai: Disrupting Speech AI with Cost-Effective Innovation
Products & Services
Ultra-fast text-to-speech model with sub-100ms latency, supporting 30+ languages and human-like emotional voices.
A full-duplex multimodal speech-to-speech model designed for natural, real-time conversations.
Small language model with <3B parameters specialized for conversational use cases and high efficiency.
Speech-to-text model series supporting 38+ languages with code-switching and emotional detection.
Market Position
Positioned as a high-efficiency alternative to large-scale models like OpenAI or ElevenLabs, emphasizing sub-100ms latency and specialized small models for enterprise production.
Leadership
Founders
Sudarshan Kamath
Previously a Senior Engineer for Self-Driving Vehicles at Bosch. Also worked as a Product Associate at Toppr. Alumnus of IIT Guwahati.
Akshat Mandloi
Co-founder and CTO. Previously an engineer at Bosch (Self-driving vehicles). Alumnus of IIT Delhi. Focused on high-efficiency model architectures.
Executive Team
Sudarshan Kamath
Co-founder & CEO
Former Bosch self-driving engineer, Toppr product lead.
Akshat Mandloi
Co-founder & CTO
Former Bosch engineer, technical lead for model efficiency.
Board of Directors
Founding Story
Founded by Sudarshan Kamath and Akshat Mandloi, who previously worked on large-scale models for self-driving cars at Bosch. They recognized that large models had latency and cost barriers for real-time voice applications. They started Smallest AI to fix the 'latency problem' by developing highly efficient, small models (<10B parameters) specifically for enterprise voice use cases.
Business Model
Revenue Model
API usage fees for models (Wave/Lightning), tiered subscriptions for the Atoms agent platform, and custom enterprise licensing.
Pricing Tiers
Base rate for low-latency TTS usage.
Tiered access based on number of concurrent requests and voice agents.
Target Markets
- Enterprise Contact Centers
- Fintech
- Healthcare
- B2C AI Applications
- Logistics
- Enterprise contact center automation
- Real estate lead generation
- Debt collection and financial services
- Healthcare and medical communication
- Sales and recruitment screening
- AI companions and celebrity clones
- Paytm Labs
- B2C startup ecosystems