Store fine-tune execution logs in file archives
When a custom fine-tuning job finishes in Cohere AI, automatically save the output performance metrics as a file inside Dropbox.
Google for Startups AcceleratorHow 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.
Cohere AI Explore Cohere AI →
TriggersFires when Cohere AI generates a response to a prompt.
Fires when a request to Cohere AI errors or times out.
Fires when a fine-tuning job in Cohere AI finishes.
Sends a prompt to Cohere AI and returns the model's response.
Uses Cohere AI to summarize a block of text.
Uses Cohere AI to classify or extract structured data from text.
Dropbox Explore Dropbox →
TriggersFires when a new file is uploaded to Dropbox.
Fires when a file in Dropbox is shared with someone new.
Fires when a folder's contents change in Dropbox.
Uploads a file to Dropbox.
Creates a new folder in Dropbox.
Shares a file from Dropbox with a link or user.
More Cohere AI + Dropbox workflows
See all Cohere AI + Dropbox integrations → · Browse the full workflow library →
Enterprise-grade security
Common questions
Can Knit build “Store fine-tune execution logs in file archives” between Cohere AI and Dropbox?
Yes — describe it in the box above and Knit's Integrations Agent researches Cohere AI and Dropbox'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.
What's the most common AI Models + Files & Storage automation?
Having Cohere AI summarize or extract key fields from a document uploaded to Dropbox, then write that structured output somewhere else automatically.
Does this work on scanned documents/images, or only text files?
Cohere AI can process scanned documents and images as well as plain text files, depending on the model's own capabilities.