Pipecat AI API

Name: Pipecat AI API
Brand: Pipecat AI API
Availability: InStock

✓ Official Vendor SpecAI/MLVoice Aibearer35 EndpointsREST

For Agents

Build real-time voice AI agents with streaming speech recognition, LLM integration, natural voice synthesis, and function calling. Supports 35 endpoints for voice pipelines, conversation management, and telephony integration.

Install Jentic One Beta

Connect the Pipecat AI API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Pipecat AI API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Pipecat AI API.

Stream audio input with real-time speech-to-text transcription and interruption detection

Integrate with LLMs (OpenAI, Anthropic, Gemini) for natural conversation understanding and generation

Synthesize natural-sounding speech with multiple voice providers (ElevenLabs, Azure, Google, Deepgram)

GET STARTED

Start building with Pipecat AI API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use Pipecat AI API for, with concrete tasks.

★ AI Phone Support Agent

Build AI-powered phone agents that handle customer support calls with natural conversation flow, function calling for order lookups, and intelligent routing to human agents. The API provides real-time STT for understanding customer requests, LLM integration for generating responses, TTS for natural speech output, and function calling to query CRM systems and databases. Agents handle interruptions naturally and maintain conversation context across topics.

Create a voice agent connected to Twilio phone number that greets callers, uses STT to understand their request, calls an order status API function when they mention an order number, and synthesizes a natural response with order details via ElevenLabs TTS

Real-Time Voice Assistant for Web Apps

Embed voice AI capabilities in web applications using WebRTC transport for low-latency voice interactions. The API handles the full voice pipeline including audio streaming, speech recognition, LLM reasoning, response generation, and voice synthesis. Ideal for virtual sales assistants, voice-enabled dashboards, accessibility features, and hands-free application control.

Initialize a WebRTC voice pipeline with browser audio input, configure Deepgram STT, OpenAI GPT-4 for conversation, and Azure TTS for responses, then stream audio back to browser with <200ms latency

Appointment Scheduling Voice Bot

Automate appointment booking over the phone with a voice agent that understands scheduling requests, checks calendar availability via function calls, confirms appointments, and sends confirmations. The agent handles complex multi-turn conversations including date/time disambiguation, service selection, and rescheduling requests. Integration with calendar APIs enables real-time availability checks.

Build a voice agent that answers incoming calls, asks for service type and preferred time, calls a calendar API to check availability, offers alternative slots if requested time is unavailable, confirms the appointment, and sends SMS confirmation

Voice Pipeline Configuration and Testing

Configure and test voice AI pipelines with different combinations of STT providers (Deepgram, AssemblyAI, Whisper), LLMs (GPT-4, Claude, Gemini), TTS engines (ElevenLabs, Azure, Google), and transport layers (WebRTC, Twilio, Telnyx). The API allows swapping components, A/B testing voice quality and latency, and monitoring pipeline performance metrics including transcription accuracy and response times.

Create three voice pipeline configurations with different TTS providers (ElevenLabs, Azure, Google), run test conversations through each, measure latency and voice naturalness scores, and select the optimal pipeline for production deployment

Key Endpoints

35 endpoints — pipecat ai provides real-time voice ai infrastructure for building voice agents, phone bots, and conversational ai applications with ultra-low latency.

METHOD

PATH

DESCRIPTION

POST

/v1/agents

Create a new voice agent

POST

/v1/agents/{agentId}/conversations

Start a conversation session

POST

/v1/pipelines

Configure voice pipeline with STT/LLM/TTS stages

POST

/v1/functions

POST

/v1/telephony/connect

Connect agent to phone number

POST

/v1/webrtc/session

Initialize WebRTC voice session

GET

/v1/conversations/{conversationId}/transcript

Retrieve conversation transcript

POST

/v1/agents

Create a new voice agent

POST

/v1/agents/{agentId}/conversations

Start a conversation session

POST

/v1/pipelines

Configure voice pipeline with STT/LLM/TTS stages

POST

/v1/functions

POST

/v1/telephony/connect

Connect agent to phone number

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Pipecat AI bearer tokens are stored encrypted in the Jentic vault and injected as Authorization headers at execution time. LLM API keys (OpenAI, Anthropic) configured in pipelines are also secured and never exposed in agent context.

Intent-based discovery

Agents search by intent such as 'create a voice agent for phone calls' or 'configure voice pipeline with STT and TTS' and Jentic returns the matching endpoint with its schema and required parameters.

Time to first call

Direct Pipecat AI integration: 2-4 days for pipeline configuration, function calling setup, and telephony integration. Through Jentic: under 1 hour — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

ElevenLabs API

Text-to-speech synthesis with natural voices used within Pipecat pipelines

Use ElevenLabs as the TTS provider in Pipecat voice pipelines for high-quality voice synthesis

Complementary

Deepgram API

Real-time speech-to-text transcription used within Pipecat pipelines

Use Deepgram as the STT provider in Pipecat voice pipelines for low-latency transcription

Complementary

Twilio Voice API

Telephony infrastructure for phone number provisioning and call routing

Use Twilio for phone connectivity and Pipecat for voice AI conversation logic

Alternative

Retell AI API

Voice AI platform with similar phone agent and conversation capabilities

Choose Retell AI for managed phone agent infrastructure; choose Pipecat for more control over pipeline components and custom integrations

FAQs

Specific to using Pipecat AI API through Jentic.

What authentication does the Pipecat AI API use?

The API uses bearer token authentication with API keys generated in the Pipecat dashboard. Each request includes an Authorization: Bearer {token} header. Through Jentic, bearer tokens are stored encrypted and injected automatically — they never appear in agent prompts or conversation logs.

What is the latency for voice responses?

Pipecat AI is optimized for sub-200ms response latency from speech input to audio output. Actual latency depends on the chosen STT provider, LLM speed, and TTS engine. Deepgram STT + GPT-4 + ElevenLabs TTS typically achieves 150-250ms end-to-end latency, which feels natural in conversation with proper interruption handling.

Can I use my own LLM instead of OpenAI or Anthropic?

Yes. The pipeline configuration accepts custom LLM endpoints that conform to the OpenAI Chat Completions API format. You can integrate self-hosted models, Azure OpenAI, or any LLM service with compatible API. Function calling requires the LLM to support tool use capabilities.

What phone providers are supported?

Pipecat AI integrates with Twilio, Telnyx, and Vonage for telephony transport. You configure your phone provider credentials and Pipecat handles the SIP/WebRTC connection, audio streaming, and DTMF handling. Inbound and outbound calling are supported with conversation recording and analytics.

How does function calling work during conversations?

You register functions with JSON schemas via POST /v1/functions. During conversation, when the LLM determines a function call is needed (e.g., 'check order status'), Pipecat executes your webhook endpoint with parameters, receives the result, and the LLM incorporates it into the response. This enables real-time API integration during voice calls.

What are the pricing and rate limits?

Pipecat AI offers a free tier with 100 conversation minutes per month. Paid plans start at $99/month for 1,000 minutes with additional per-minute charges beyond quota. Rate limits are 100 concurrent conversations for standard plans. Enterprise plans offer custom limits and SLA guarantees.