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Every interaction between an AI Assistant and an end user is stored as a conversation in AI Conversations. Conversations are keyed by channel and by the two endpoints of the conversation — the assistant’s target (a phone number, SIP URI, or other identifier) and the end user’s target — and the same assistant can have several independent conversations with the same end user, one per channel.

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Keying model per channel

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Conversation metadata

Each conversation carries identifying metadata you can read on every list and get response: The same fields are available to the assistant’s instructions and tools as dynamic variables: {{telnyx_conversation_channel}}, {{telnyx_agent_target}}, and {{telnyx_end_user_target}}.

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One pair, one conversation per channel

A single number pair — one assistant number and one end-user number — can have several concurrent or sequential conversations, one per channel. A phone call to the assistant’s number creates a phone_call conversation for that call, while texts with the same number pair continue in their own long-lived sms_chat conversation. The two records are independent: closing the call does not close the text conversation, and the assistant’s memory can span both by querying on telnyx_end_user_target without a channel filter.

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Querying conversations by channel or participant

The List Conversations endpoint filters on any metadata field using PostgREST-style parameters. All SMS conversations with one end user:
Every conversation — calls and texts — between one number pair:
Phone-call conversations created in a window:
Message rows carry channel metadata too: a turn recorded with telnyx_conversation_channel: sms_chat inside a conversation whose own channel is phone_call did not come from the call. When inspecting a transcript, read the channel on both the conversation and each message.