Retell AI
By Retell AI
Retell AI is a developer platform for building and deploying voice AI agents that can conduct real-time phone conversations, combining speech recognition, a large language model (LLM), and text-to-speech into a low-latency voice pipeline.
Definition
Retell AI is a developer platform for building and deploying voice AI agents that can conduct real-time phone conversations, combining speech recognition, a large language model (LLM), and text-to-speech into a low-latency voice pipeline.
Overview
Retell AI targets teams that want to add conversational voice capability to products without stitching together speech and language infrastructure themselves. It provides an API and dashboard for defining a voice agent's persona, conversation flow, and knowledge base, then exposes that agent over telephony (inbound/outbound calls) or embedded web/app calling. Under the hood, a Retell agent chains three stages for every conversational turn: speech-to-text transcribes the caller's audio, an LLM — often a model like those behind ChatGPT or Claude — generates a response grounded in the agent's configured prompt and tools, and a text-to-speech engine converts that response back into natural-sounding audio. Latency is the central engineering challenge in this category, since a voice agent that pauses too long before responding breaks the illusion of a real conversation, so platforms like Retell AI optimize heavily for streaming and interruption handling (letting a caller talk over the agent naturally). Retell AI fits into the broader wave of voice-first AI agent tooling alongside companies like Vapi, aimed at use cases such as automated customer support lines, appointment scheduling, and outbound sales or survey calls. Developers typically connect it to a CRM or backend via function/tool calling so the agent can look up account information or book appointments mid-call, similar in spirit to how a text-based agent uses RAG or APIs to ground its answers.
Key Features
- Real-time speech-to-text and text-to-speech pipeline optimized for low latency
- Support for inbound and outbound phone calls via telephony integration
- Configurable agent prompts, personas, and conversation flows
- Function/tool calling so agents can query external systems mid-call
- Interruption handling so callers can talk over the agent naturally
- Call analytics, transcripts, and recording for QA and monitoring
- Integrations with popular LLM providers for the underlying language model