AI Chatbot for Google Sheets: the answers are already in your spreadsheet

Why a spreadsheet is the best answer source you already own

A website page is prose. It says "we ship across Europe, delivery times vary by country" — true, and useless to the person who wants to know about Norway. The sheet behind that sentence has forty rows and every one of them is an exact answer.

That is the whole reason spreadsheet uploads exist. When Asyntai ingests a normal document it cuts the text into overlapping blocks and hopes the right sentence lands in the right block. A spreadsheet does not need that guesswork: the file already tells the system where one fact ends and the next begins. So each row is stored as its own chunk, and a question about Norway retrieves the Norway row instead of a paragraph that mentions eleven countries.

Price lists, size charts, opening hours per branch, warranty terms per product line, a course catalogue, a room rate table — anything you maintain in rows is a good fit. And you keep maintaining it where you always did.

How to turn a Google Sheet into chatbot knowledge

Be clear about one thing before you start, because it changes how you work: Asyntai does not connect to Google. There is no OAuth screen, no Google account token, no background polling of your document. You export the file and upload it, and what the assistant knows is a snapshot of that file.

Doing it from the API instead

If you would rather not touch the dashboard every month, the same upload exists as an endpoint. It takes a multipart/form-data POST with the file in a field called file, and an optional website_id when your account has more than one site. API access needs a paid plan.

The key can also travel as an X-API-Key header if that suits your tooling better. One behaviour difference is worth knowing: where the dashboard refuses an oversized file, the API accepts it and simply stops at your plan's row limit — so check rows_processed against what you sent. Full reference in the API documentation.

That endpoint is what makes a scheduled refresh possible. A monthly job in your automation tool of choice can export the sheet, POST it here, and delete the previous entry — which is as close to a sync as this gets, and it is honest about being a re-upload.

What a good chatbot spreadsheet looks like

Because each row becomes one chunk, the row has to make sense on its own. Asyntai builds the chunk text by pairing every column name with its value — Question: Do you ship to Norway? then Answer: Yes, 4–6 working days. — and empty cells are skipped. So your column headers are not decoration. They are labels the AI reads.

The same shape works for catalogues: Product, SKU, Price, Stock, Lead time. One product per row, one row per answer.

• One idea per row. An answer split over three rows retrieves as three fragments, and each fragment reaches the assistant without the other two.
• Name the columns properly. Delivery time beats Col C, because the header text ends up inside the chunk the AI reads.
• No merged cells or spacer rows. A CSV export flattens merges into blanks, and blank cells are dropped from the row text.
• Skip layout columns. Notes to yourself, colour codes and internal owners add noise to every single chunk. Delete them from the export.
• Keep one topic per file. Separate uploads for the price list and the FAQ are easier to replace when only one of them changes.

The other direction: writing chats back to a sheet

Plenty of people want the reverse flow — every conversation appended as a row so the team can read it in Google Sheets. That works, but it needs one piece in the middle, and it is fair to say why.

Asyntai webhooks fire on events such as conversation.started and escalation.requested. They POST a fixed body with an event field and a payload field, signed with an X-Webhook-Signature header. You cannot add your own headers, so the webhook cannot present a Google OAuth token and cannot call the Google Sheets API by itself.

The fix is a connector. Point the webhook URL at a scenario in Make, a workflow in n8n, a Zap in Zapier, or a Google Apps Script web app you deploy yourself. That step holds the Google credentials and appends the row. In a visual tool the mapping is a few fields:

Worth doing if a sheet is where your team already looks. Just do not expect it without the middle step.

What a spreadsheet-fed chatbot does well

Google Sheets chatbot questions

Related pages

Other ways to feed the assistant and reach it from the tools you already run.