PERSONAL PRODUCTIVITY
AI-suggested Dropbox renames with Airtable rename log
Uses an LLM to infer the correct canonical filename for messy Dropbox uploads, applies the rename.
How it runs
The automated pipeline, trigger to output.
- TriggerDropbox file-added webhookDropbox
- ActionLLM infers canonical name + confidenceOpenAI
- LogicGate on confidence threshold
- ActionRename file in DropboxDropbox
- OutputLog old/new mapping in AirtableAirtable
What it does
Some filenames are too messy for fixed rules — abbreviations, typos, or free-text descriptions. This workflow sends the original name (and folder context) to an LLM that returns a structured canonical name, then renames the file and records the mapping in Airtable as a permanent rename log.
When to use it
Use it when uploads come from outside parties or non-standard tools and rigid pattern rules cannot reliably reshape them. The AI handles ambiguous cases; the Airtable log gives you a full old-to-new history if you ever need to trace or undo a change.
How it works
- 1A Dropbox webhook fires when a file is added.
- 2The LLM receives the filename plus folder context and returns a structured canonical name with a confidence score.
- 3A check gates on confidence — low-confidence results are flagged for review instead of renamed.
- 4Dropbox renames high-confidence files to the suggested name.
- 5Airtable logs the old name, new name, confidence, and timestamp for every processed file.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect AirtableBases, tables, views, automations.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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