Send custom completions back to chat visitors
When a conversation starts in EmbedAI, generate a completion in DeepSeek and send a tailored message directly back to the visitor.
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How Knit builds this workflow
The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.
EmbedAI Explore EmbedAI →
TriggersFires when a new chat or conversation begins in EmbedAI.
Fires when EmbedAI captures a lead during a conversation.
Fires when EmbedAI escalates a conversation to a human.
Sends a message to a user through EmbedAI.
Asks EmbedAI a question against its knowledge base and returns the answer.
Uses EmbedAI to summarize a chat transcript.
Opens a support ticket from an EmbedAI conversation.
DeepSeek Explore DeepSeek →
TriggersFires when DeepSeek generates a response to a prompt.
Fires when a request to DeepSeek errors or times out.
Fires when a fine-tuning job in DeepSeek finishes.
Sends a prompt to DeepSeek and returns the model's response.
Uses DeepSeek to summarize a block of text.
Uses DeepSeek to classify or extract structured data from text.
More EmbedAI + DeepSeek workflows
Extract lead details during chatbot conversations
When a new lead is captured in chat via EmbedAI, automatically run the conversation text through DeepSeek to classify intent and extract key contact metadata.
See details
Alert support agents when model fine-tuning completes
When a fine-tune job completes in DeepSeek, automatically send a message through EmbedAI to notify AI administrators that the updated model is ready.
See details
See all EmbedAI + DeepSeek integrations → · Browse the full workflow library →
Common questions
Can Knit build “Send custom completions back to chat visitors” between EmbedAI and DeepSeek?
Yes — describe it in the box above and Knit's Integrations Agent researches EmbedAI and DeepSeek's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.
How long does it take to build?
Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.
How does connecting EmbedAI to DeepSeek expand chatbot capabilities?
Connecting EmbedAI to DeepSeek allows your chatbot to tap into advanced AI models for deeper context, sentiment classification, and sophisticated text generation beyond standard scripted responses.
Can EmbedAI notify operators if a backend model process encounters an issue in DeepSeek?
Yes, when a model run fails in DeepSeek, you can send an automated message or alert through EmbedAI to notify system administrators.