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Copy file name to clipboardExpand all lines: src/pages/docs/platform/products/index.mdx
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@@ -121,7 +121,7 @@ AI Transport is a good fit when:
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* You need to manage AI chat sessions with identity and resumability.
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* You want to fan out AI-generated content to multiple subscribers.
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If your chat is primarly between humans, even when AI moderates or assists behind the scenes, then consider the [Chat SDK](#chat).
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If your chat is primarily between humans, even when AI moderates or assists behind the scenes, then consider the [Chat SDK](#chat).
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### Why use purpose-built SDKs
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***Consider message ordering**: Messages on SDK-managed channels and custom Pub/Sub channels are independent; design your application accordingly.
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***Handle connection state once**: The underlying Realtime client manages connection state; don't add redundant connection handling for custom features.
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## Choosing between AI Transport and Chat SDKs <aid="ait-vs-chat"/>
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## Choosing between AI Transport and the Chat SDK <aid="ait-vs-chat"/>
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AI Transport and the Chat SDK both handle conversations but for different types of users.
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The AI Transport SDK and the Chat SDK both handle conversations but for different types of users and operations.
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The Chat SDK provides support for common chat application operations: not just publishing and subscribing to messages, but moderation, typing indicators, emoji reactions, and editing or deleting messages.
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The AI Transport SDK enables interactions with AI agents that go beyond those operations. It is built for human-to-agent and client-to-agent interactions that support an agentic loop, tool calls, human-in-the-loop, interruption and steering, as well as streamed responses. Simple editing of messages, as supported by the Chat SDK, is not sufficient for agent applications, because of the need to support regeneration of responses and the resultant forking of conversations. Similarly, agentic applications have a much richer need to indicate progress than the simple typing indicators used for human chat, and agentic interactions such as runs and steps are an intrinsic part of the control flow of an agent session, not just a visual indicator.
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| You are building | Use |
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| --- | --- |
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| A user conversing with an AI agent: streaming responses, multi-turn, across devices |[AI Transport](/docs/ai-transport)|
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| People conversing with each other: support staffed by humans, group chat, livestream chat |[Chat SDK](/docs/chat)|
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The Chat SDK provides support for operations that are commonly needed in chat applications: not just publishing and subscribing to messages, but moderation, typing indicators, emoji reactions, and editing and deleting messages.
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AI Transport supports interactions with AI agents that go beyond this. It is built for human-to-agent and client-to-agent interactions that support an agentic loop, tool calls, human-in-the-loop, interruption and steering, as well as streamed responses. Simple editing of messages, as supported by the Chat SDK, is not sufficient for agent applications, because of the need to support regeneration of responses and the resultant forking of conversations. Similarly, agentic applications have a much richer need to indicate progress than the simple typing indicators sufficient for human chat, and agentic interactions such as runs and steps are an intrinsic part of the control flow of an agent session, not just a visual indicator.
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In support scenarios, if an AI answers the user then reach for AI Transport, even when a human can take over the conversation. If people staff the conversation, reach for the Chat SDK, even when AI moderates or assists behind the scenes.
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The two products run on the same Ably platform but are separate today, so you can [combine](#combine-pubsub) either of them with Pub/Sub but not with each other. Closer integration between AI Transport and Chat is coming soon, which will give applications that need both AI-driven and human-to-human messaging a simple implementation path.
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