
Smallest.ai
Real time voice artificial intelligence platform building small efficient models.

About Smallest.ai
Smallest.ai: Real-time Voice AI, Built to Scale
Smallest.ai is an artificial intelligence platform focused on driving the future of small, efficient multi-modal models. The platform develops models under 10 billion parameters that are designed to outperform larger language models while utilizing dramatically lower GPU usage and achieving ultra-low latencies.
Key Features
- Lightning Text-to-Speech: Generates hyper-realistic audio in over 30 languages with thousands of local accents, voice cloning, and a time-to-first-byte as low as 100ms.
- Electron Small Language Model: A conversational model with less than 3 billion parameters, featuring a 45ms time-to-first-token and built-in protection against NSFW content and prompt attacks.
- Pulse Speech-to-Text: Transcribes audio across 38+ languages with code-switching, emotion detection, speaker identification, and interruption handling.
- Hydra Speech-to-Speech: A full-duplex multimodal model supporting long context, tool calling, and highly emotional human-like voices.
- Atoms Agentic Platform: Allows users to create, test, deploy, and analyze self-learning multi-modal AI agents across voice, email, chat, and social channels.
- Enterprise Security: Secured by SOC 2 Type 2, HIPAA, PCI, GDPR, and ISO-aligned compliance standards.
- Developer SDKs: Provides Node.js and Python SDKs for building and orchestrating AI workflows.
Use Cases
- Conversational AI: B2C notetakers, AI companions, AI celebrity clones, B2B collections, lead qualifications, and customer support.
- Edge Computing: Custom chips, specialized hardware, and mobile devices.
- Enterprise Production: High-volume production use-cases handling billions of conversations with sub-400ms average latency.
Getting Started
Website: https://smallest.ai/
Smallest.ai provides highly efficient, specialized machine intelligence capable of handling enterprise-scale operations. By focusing on small models that continuously learn and operate asynchronously, the platform delivers high domain accuracy and cost reductions for complex voice and text automation.