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://jentic.com/install.sh?src=apis&api=%2Fapis%2Fpipecat.ai%2Fpipecat-ai" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fpipecat.ai%2Fpipecat-ai" | 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)

Execute function calls during conversations for API lookups, database queries, and system actions

GET STARTED

Start building with Pipecat AI API

Explore with Jentic One

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

POST

/v1/webrtc/session

Initialize WebRTC voice session

GET

/v1/conversations/{conversationId}/transcript

Retrieve conversation transcript

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring Pipecat AI by hand means managing its bearer token, sequencing agent, pipeline, and telephony calls, and handling retries yourself. Through Jentic you install once, import Pipecat AI from the API Directory, store the token once, and your agent calls it.

Permission scoping

Pipecat AI puts the agent id in the URL path (/v1/agents/{agentId}/conversations), so a rule can pin your agent to one Pipecat agent and its conversations. You choose the operations it may call, so pipeline or function changes are not included unless you add them.

Credential isolation

Your Pipecat AI bearer token is stored once, encrypted, by your own Jentic One instance and injected as an Authorization header at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'create a voice agent for phone calls' or 'fetch a conversation transcript', and Jentic returns the matching Pipecat AI operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

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.

Can I limit what my agent is allowed to do with the Pipecat AI API?

Yes. Because you run Jentic One yourself, your own rules decide which Pipecat AI operations and credentials the agent may use. Since the agent id sits in the URL path, such as /v1/agents/{agentId}/conversations, you can pin the agent to a single Pipecat agent and its conversations. You can also choose exactly which operations it may call, so pipeline configuration via /v1/pipelines or function registration via /v1/functions stays off limits unless you explicitly allow it.

Pipecat AI API

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

Official vendor OpenAPI document · agent-readyAI/MLSpeechbearer35 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.

Use for: I need to create a voice agent that answers customer support calls, Build a phone bot for appointment scheduling with calendar integration, Configure speech-to-text with interruption detection for natural conversations, Set up a voice pipeline with OpenAI GPT-4 and ElevenLabs TTS

Not supported: Does not provide phone number provisioning, call recording storage, or conversation analytics dashboards - use for real-time voice AI pipeline orchestration and conversation management only.

Pipecat AI provides real-time voice AI infrastructure for building voice agents, phone bots, and conversational AI applications with ultra-low latency. The API handles speech-to-text streaming, large language model integration, text-to-speech synthesis, function calling, and WebRTC transport for voice interactions. Built for developers creating AI phone agents, voice assistants, IVR systems, and real-time conversational interfaces with natural interruption handling and sub-second response times.

Jentic One on Github View OpenAPI Document

Connect the Pipecat AI API to your agent

Capabilities

Start building with Pipecat AI API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Pipecat AI API