Hume AI

What is Hume AI?

Hume AI provides infrastructure for creating and evaluating conversational voice applications. Its best-known product, the Empathic Voice Interface (EVI), supports real-time speech-to-speech interaction rather than requiring an application to assemble separate speech recognition, language-model, and voice-generation services.

A typical Hume application streams a user's audio to the platform and receives transcripts, expression information, text responses, and generated speech. Developers can configure the system's instructions, voice, language model, turn-taking behavior, tools, and contextual information. This makes Hume closer to a voice-agent platform and developer API than to a consumer chatbot.

What Hume AI actually does

Real-time voice agents

EVI is designed for spoken conversations in which timing and turn-taking matter. Applications can support interruptions, pauses, resumptions, contextual variables, chat history, and tool calls. A developer might use these capabilities for a customer-service agent, a coaching experience, an educational application, or another product in which users interact primarily through speech.

Hume can handle expressive speech generation while an external or custom language model controls response content. Supported model connections have included providers such as Anthropic, OpenAI, Google, Fireworks, and custom language models. The exact choices depend on the API version and configuration.

Expressive speech and voice creation

Hume includes a library of voices, voice design from textual descriptions, and voice cloning from recorded samples. Voice cloning should be used only with appropriate permission and consent. The platform's emphasis is not simply on converting text into intelligible audio; it also aims to represent qualities such as tone, rhythm, and timbre.

This places Hume alongside specialized voice platforms such as ElevenLabs, Cartesia, and Resemble AI, but Hume's broader product scope includes live conversation, expression measurement, and voice-agent evaluation.

Expression measurement

Hume analyzes expressive characteristics in audio and text. Developers and researchers can use these measurements to study how a conversation sounds and how vocal qualities change across interactions. This is useful when evaluating whether an agent's delivery is appropriately timed, natural, expressive, or contextually suitable.

Evaluation infrastructure

Hume also addresses the testing problem that comes with voice agents. Its evaluation capabilities are intended to help teams generate tests, compare systems, identify conversational failures, and assess qualities such as latency, naturalness, expression, and contextual appropriateness. This distinguishes it from a basic speech-to-text or text-to-speech service, which may produce audio but provide little support for evaluating the complete conversation.

How developers use the platform

Implementation generally begins with an account and a voice configuration. The developer selects a voice and language model, defines system behavior, and optionally adds tools, context, dynamic variables, web search, or application-specific functions. The client then connects through Hume's web or API infrastructure, commonly using real-time WebSocket communication for an ongoing conversation.

Hume provides browser-oriented workflows and SDK or integration options for technologies including React, TypeScript, Python, .NET, and Swift. It can also be connected to communications and application infrastructure such as Twilio, Daily, or Agora, according to the supplied product documentation. Teams building a phone agent may also compare it with more deployment-focused platforms such as Vapi, Retell AI, or Deepgram; Hume's distinguishing focus is expressive interaction and evaluation rather than only telephony or transcription.

Languages and outputs

EVI 4-mini is documented for English, Japanese, Korean, Spanish, French, Portuguese, Italian, German, Russian, Hindi, and Arabic. EVI 3 supports English and Spanish. Language availability for other expression-measurement and text-to-speech models can vary, so teams should verify support for a specific production configuration.

Outputs can include speech, audio streams, transcripts, text responses, expression measurements, and evaluation results. Hume is therefore primarily a voice and audio platform with text and analytical outputs, not an image, video, document, or general-purpose content-generation product.

Pricing and access

Hume offers a free plan and paid subscriptions. The free tier includes limited text-to-speech and EVI usage, including approximately 10 minutes of TTS usage and 5 minutes of EVI usage, with one concurrent connection. It also includes voice creation and use within the stated plan limits.

Paid plans currently start at $3 per month for Starter. Public plans also include higher tiers such as Creator, Pro, Scale, and Business, with listed prices ranging from $14 to $500 per month before any applicable promotions or usage charges. Plans differ in included EVI minutes, TTS characters, concurrent connections, and request limits. Additional usage may be billed by minute or by character, while Enterprise pricing is custom.

The pricing model is consequently a combination of subscription access and consumption limits. A small prototype may fit within the free plan, but a production voice application should estimate conversation minutes, speech generation, concurrency, and overage costs before choosing a tier.

Privacy and an important API limitation

Hume's API Data Usage Policy states that customer-submitted API data is not used to train Hume's own models or improve its service offerings. Data submitted through the Custom Model API is described as being used for the specific customer's model rather than for Hume's general systems or other customers' models. Consumer services such as the Playground are governed separately, so organizations should review the applicable terms for the exact workflow they plan to use.

Hume describes enterprise offerings with security and compliance options including SOC 2 Type II, GDPR, and HIPAA-related support. Retention depends on the product and endpoint. The documentation also states that data associated with the legacy TTS and EVI APIs is scheduled for permanent deletion after November 13, 2026.

This sunset is a significant consideration. Hume's documentation says access to the legacy EVI and TTS APIs will end on that date, along with associated account data. Anyone starting a new project should confirm which current products and APIs are covered, assess migration requirements, and avoid assuming that an older integration will remain available indefinitely.

Who should use Hume AI?

Hume is a strong fit for developers, researchers, and product teams building voice-first applications where expression, conversational timing, and evaluation matter. It is particularly relevant for customer-support agents, coaching and education experiences, healthcare conversations, interactive assistants, and teams testing the quality of speech-based AI.

It is less suitable for someone who wants a ready-made personal chatbot, a general writing assistant, a visual content generator, or a simple no-code automation tool. Although Hume offers browser tools and some no-code access, its most substantial capabilities involve API configuration, model selection, real-time audio handling, and application development.

Bottom line

Hume AI combines real-time voice-agent infrastructure with expressive speech, voice creation, emotion-related measurement, and evaluation. Its main value is for teams that need to build and assess spoken AI experiences rather than merely generate isolated audio clips. The technical setup, usage-based pricing, model and language variation, and planned retirement of the legacy EVI and TTS APIs are important limitations to account for before deployment.