smallest.ai

smallest.ai is a text-to-speech tool. Smallest AI offers text-to-speech, speech-to-text, speech-to-speech and a small language model, plus a voice agent platform. It targets developers and enterprises building low-latency phone and conversational products, with compliance certifications and on-premise options.

Smallest AI is a voice AI platform that bundles speech models and an agent builder into one stack. The model lineup covers text-to-speech (Lightning V3.1 Pro, quoted at 100 ms latency across more than 15 languages), speech-to-text (Pulse Realtime, covering 38 languages with emotion and speaker detection), a small language model called Electron, and Hydra, a native speech-to-speech model. Voice cloning and a public voice library sit alongside these. The audience is mainly developers and enterprises building phone and conversational products. On the developer side, the homepage shows a plain HTTP request that posts text, a voice ID, a sample rate and an output format to the API and saves the returned audio file, with access handled through an API key created in the account settings. On the product side, an agent platform lets teams configure an agent, choose a voice, set languages and go live from one interface, with a playground for testing. Industry pages target healthcare, real estate, travel and hospitality, automobile, banking and e-commerce, and an on-premise option exists for organisations that cannot send audio to a hosted service. In practice the workflow starts with the interactive demo or the playground, moves to an API key, and then to either direct model calls or a configured agent. Enterprise buyers are routed to a sales form that promises a forward-deployed engineer and large concurrent call volumes. Security claims include ISO 27001, SOC 2 Type 2, GDPR and HIPAA compliance. Customer stories cite a speech-to-text deployment at Pocket and a collections-call use case at Kogta. Among alternatives, it competes with dedicated speech vendors and with voice agent orchestration platforms. Its differentiator is owning the whole chain: recognition, language model, synthesis and a speech-to-speech option from one vendor, which can reduce latency and integration work. The trade-off is dependence on a single provider for every layer, and the homepage leaves detailed pricing to a separate page.