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Vapi · Excel Guide

Bulk Create Vapi Evals From an Excel workbook of Test Scenarios

2026-05-14
5 min read

The Scenario

You are the QA engineer on a team shipping a new customer support voice assistant. Your test plan has 20 conversation scenarios in an Excel workbook: column A is the eval name, column B is the scenario description, column C is the mock conversation JSON.

Creating 20 Vapi evals by hand means 20 trips through the Vapi dashboard or 20 API calls you have to write and fire one at a time. You have a sprint demo tomorrow and this was supposed to be done yesterday.

The bad version:

  • Open the Vapi dashboard, navigate to Evals, click New Eval
  • Copy the eval name from column A of your workbook, paste it into the form, copy the description from column B, paste it, format the mock conversation JSON from column C into whatever the form expects
  • Save, go back to the list, start the next one
  • Realize on eval 12 that the form has a character limit on descriptions and three of yours are too long

The sprint demo is in 14 hours. You have 20 evals to create. This is not a good use of those hours.

The Easy Way: One Prompt in SheetXAI

SheetXAI is an AI agent that lives inside your Excel workbook. It reads your eval definitions directly from the worksheet and creates each one in Vapi through the built-in integration — one operation for all 20 rows.

Create Vapi evals for every row in my Excel sheet — column A is the eval name, column B is the scenario description, column C is the JSON mock conversation

What You Get

  • All 20 evals created in Vapi in a single operation
  • Each eval gets its name, description, and mock conversation from the corresponding row in the workbook
  • SheetXAI reports which evals were created successfully and flags any rows that failed

What If the Data Is Not Quite Ready

Some rows are draft scenarios not ready for creation — marked with 'draft' in column D

Read my Excel sheet where column A is eval name, column B is description, column C is mock conversation JSON, column D is status — create a Vapi eval for every row where column D is not 'draft'

The mock conversation JSON in column C has inconsistent formatting

Read my Excel sheet where column A is eval name, column B is description, column C is mock conversation JSON — normalize the JSON in column C to valid format before creating each Vapi eval

You need to create evals in batches of 5 to stay within rate limits

Read my Excel sheet where column A is eval name, column B is description, column C is mock conversation JSON — create Vapi evals for rows 2 through 6 only

Validate, create, and log results in one shot

Read my Excel sheet where column A is eval name, column B is description, column C is mock conversation JSON — skip any row where column A or column C is empty — create Vapi evals for all remaining rows and write 'created' or the error message into column D of each row

Building the validation and the result logging into the prompt means you finish with a workbook that tells you exactly what was created and what was not, without a second operation.

Try It

Get the 7-day free trial of SheetXAI and open the Excel workbook where your conversation test scenarios live, then ask it to create the Vapi evals from the rows. For related tasks, see how to export your scorecard inventory or export the full call log.

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