An ElevenLabs Alternative for Full Voice Agents, Not Just Voices cover illustration

## A good voice is necessary and nowhere near sufficient Speech synthesis is the last stage of a voice agent, and it is the stage people judge a demo on. But a production call is won or lost upstream: understanding why someone called, deciding what to do, looking the answer up somewhere real, taking an action, and knowing when to hand off — all inside the half-second before a caller decides this is not working. A flawless voice reading a wrong answer is still a failed call, and a flawless voice saying 'I cannot help with that' is an expensive way to route to a human. Overview of An ElevenLabs Alternative for Full Voice Agents, Not Just Voices

Overview of An ElevenLabs Alternative for Full Voice Agents, Not Just Voices

## The whole pipeline, wired as one system Persistence is a complete voice agent platform: speech recognition, language understanding, action execution and speech synthesis, running as a single streaming system rather than four services chained by API calls. Tokens flow from recognition into the model as they arrive, and audio generation begins before the model finishes its response. Median end-to-end latency is under 100ms. Assembling the equivalent from separate vendors means a network hop between every stage, and every hop is silence the caller hears. ## Voice stays a choice You still get 100+ voices across 50+ languages, and you keep the ability to route to whichever synthesis engine performs best for a given use case — ElevenLabs, Cartesia or Deepgram Aura. The same applies to the language model: choose which one handles each call type, with fallbacks configured for capacity events. Being a platform rather than a single vendor's pipeline means the voice decision stays reversible. ## Design the conversation itself The part that determines whether a call works is the conversation design: what the agent asks, in what order, what it does when the answer is unexpected, and where it gives up and fetches a human. Persistence puts that on a canvas — branching paths, decision logic, fallback routes — or lets you start from a single prompt for simpler cases and add structure later. ## Answers grounded in your own content Connect documentation, webpages and databases as a knowledge base so the agent answers from your current source of truth. This is what separates an agent that says 'our returns window is 30 days from delivery' because that is what your policy page says today, from one that says it because it sounds plausible. ## Actions, not just responses Mid-conversation the agent can call functions and tools: check availability and book, look up an order, update a CRM record, trigger a workflow, transfer to a human with the context already attached. A call that ends in a completed action is worth more than a dozen that end in a well-pronounced apology. ## Test the conversation before customers do Simulate hundreds of calls against edge cases and accents, compare versions on the same suite, and roll back instantly when a change underperforms. Voice quality is easy to evaluate by listening once. Conversation quality needs to be tested at volume. ## Real phone numbers, real channels Provision a phone number inside the platform or bring your own SIP trunk, and deploy the same agent across phone, web chat and SMS without rebuilding it per channel. The gap between 'the demo sounded great' and 'it is answering our support line' is mostly this. ## One agent, every channel Customers do not think in channels. Multi-channel deployment means the same knowledge, the same logic and the same actions apply whether someone called, messaged or texted — rather than three separate implementations drifting apart over time. ## Pay-as-you-go from the first call USD 10 in free credits, pay for what you use, no contract. Put an agent on a number and hear the whole pipeline rather than just the voice. ## Frequently asked questions Speech synthesis is the last stage of a voice agent, and it is the stage people judge a demo on. But a production call is won or lost upstream: understanding why someone called, deciding what to do, looking the answer up somewhere real, taking an action, and knowing when to hand off — all inside the half-second before a caller decides this is not working. Persistence is a complete voice agent platform: speech recognition, language understanding, action execution and speech synthesis, running as a single streaming system rather than four services chained by API calls. Tokens flow from recognition into the model as they arrive, and audio generation begins before the model finishes its response. You still get 100+ voices across 50+ languages, and you keep the ability to route to whichever synthesis engine performs best for a given use case — ElevenLabs, Cartesia or Deepgram Aura. The same applies to the language model: choose which one handles each call type, with fallbacks configured for capacity events. The part that determines whether a call works is the conversation design: what the agent asks, in what order, what it does when the answer is unexpected, and where it gives up and fetches a human. Persistence puts that on a canvas — branching paths, decision logic, fallback routes — or lets you start from a single prompt for simpler cases and add structure later. ## Try Persistence Design, test, and deploy production-ready voice agents. ## Continue reading