What is your goal?
I am building an AI-assisted workflow to analyze and process research notes into structured data in Airtable for easy scanning.
What is the problem & what have you tried?
I have built several scenarios to automate an editorial workflow that processes research notes and uses AI to summarize and feed responses into Airtable. All scenarios so far have failed to produce usable text in Airtable, and I have abandoned all but the most recent build. The trigger is when a new .doc file uploads in a Google Drive folder. Each .doc file contains research for a given article topic (notes, links, thoughts, etc). The scenario should pass that file to Gemini (2.5 Flash) for analysis, and Gemini should output summarized data into Airtable. What should be a fairly simple automation has been a nightmare of endless errors. Sometimes they are rate limit errors, so I upgraded my Google API to a paid billing tier. Everything else in the automation chain is free tier for now. The biggest error seems to be that Gemini is reading text from the original document as data. I tried inserting filters and/or modules to convert to .txt before analysis, but no luck. Gemini can handle summarizing these documents when I feed it an individual .doc file directly, but once Gemini is in the middle of a Make scanario, it canβt process the information and get it into Airtable. The endpoint should be an Airtable table with each document/article file represented by one row with multiple columns for the analyzed data. Instead, it just outputs irrelevant information, or none at all. I have not even added the Airtable module in the most recent build (see attached) because it seems like the information is not being processed. I have added Airtable in previous Scenarios, along with much more elaborate input prompts, but that would seem pointless in this one if the output is not useful. Frustrated and about to give it up.
Note: Not a coder here. Please keep responses easy to understand.
Thanks!!
