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Bananaflow is a platform for building and running voice AI agents. You define a conversation flow, connect a phone number, and Bananaflow handles the rest – transcribing the caller’s speech (STT), generating intelligent responses (LLM), speaking them back in a natural voice (TTS), and returning structured results when the call ends.

The core loop

Key components

Workflows (Agents) The conversation logic. A workflow is a graph of nodes (conversation steps) connected by edges (conditional transitions). You define what the agent says, when it moves on, and what data it collects. Runs Every execution of a workflow creates a run. The run record holds the transcript, recording, extracted data, and cost information. Telephony The phone infrastructure. Bananaflow connects to your telephony provider (Twilio, Vonage, etc.) to place and receive calls. The audio streams between the caller and Bananaflow in real time. Transcriber (STT) Converts the caller’s speech to text in real time. The transcript drives both the LLM and the final run record. LLM Processes the transcript and the active node’s prompt to generate the agent’s next response. It also evaluates edge conditions to decide when to move the conversation forward. Voice Synthesizer (TTS) Converts the LLM’s text response to audio and streams it back to the caller. You pick a voice for each agent, and Bananaflow manages the transcriber, LLM, and speech models behind it.

How it fits together

When you trigger a call:
  1. Bananaflow instructs your telephony provider to dial the number
  2. When the caller answers, a real-time audio pipeline opens
  3. The caller’s speech is transcribed to text
  4. The transcript is sent to the LLM with the active node’s prompt and conversation history
  5. The LLM responds – the response is synthesized to audio and streamed to the caller
  6. When an edge condition is met, Bananaflow transitions to the next node
  7. When an end node is reached, the call ends
  8. Post-call: context is extracted, webhooks fire, the run record is saved

Next steps

Workflows & Agents

How the conversation graph works

Calls & Runs

The lifecycle of a call

Context & Variables

How data flows through a conversation

Campaigns

Running agents at scale