The Scenario
You are a fleet manager at a logistics company. The company just transitioned 45 vehicles of its delivery fleet to electric. The vehicles are in the Fleet tab of an Excel workbook with make, model, and year in columns A, B, and C. Finance needs a total-cost-of-ownership model by end of next week and it cannot be built without battery capacity, charging power, and electric range for each vehicle.
Your procurement lead spent two afternoons last week trying to pull specs from manufacturer websites. Three vehicles are discontinued models with no current web page.
The bad version of this week:
- Procurement lead opens the Tesla website, finds the Model 3 specs, copies battery capacity
- Moves to the Rivian page, different format, different unit
- Can't find the discontinued Nissan LEAF 2019 page, falls back to a forum post
- By Wednesday he has 20 of 45 vehicles done
- Finance builds the model on 20 vehicles and calls it a representative sample.
The clean version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook. It reads your EV inventory and calls the API Ninjas EV specs endpoint for each vehicle, writing battery capacity, charging power, and range to the Fleet tab.
Open the SheetXAI sidebar and type:
For each EV make and model in columns A and B of the Fleet tab, look up the battery capacity, max charging power, and electric range from API Ninjas and fill columns D, E, and F.
SheetXAI calls the EV specs endpoint for all 45 rows and writes three fields per vehicle. Discontinued models get flagged instead of silently returning wrong data.
What You Get
A complete EV fleet spec workbook ready for the TCO model:
- Column D: Battery capacity (kWh)
- Column E: Max charging power (kW)
- Column F: Electric range (miles)
Finance now has defensible specs for all 45 vehicles, not a 20-vehicle sample sourced from forum posts.
What If the Data Is Not Quite Ready
EV fleet workbooks accumulate inconsistencies. SheetXAI handles them inline.
When make/model names don't match the API format
Your workbook uses display names like "Tesla Model 3 LR."
Normalize the make and model names in columns A and B of the Fleet tab to API Ninjas standard format before fetching EV specs. Write the normalized model name into column C, then fill battery capacity, max charging power, and range into columns D, E, and F.
When some rows are not EVs
Your workbook has a mix of EVs and remaining ICE vehicles.
For rows where column C (fuel type) is "Electric" or "BEV," fetch EV specs from API Ninjas and fill columns D–F. For all other rows, write "NOT EV" in column D and leave E and F blank.
When you want to add a range-anxiety flag
Your longest delivery route is 280 miles. Any vehicle with range under 300 miles needs a flag.
After writing electric range into column F, add "Range Caution" in column G for any vehicle where column F is below 300 miles.
When the full TCO prep run is one prompt
Forty-five EVs, mixed naming, some non-EVs, range flags, and a cost-per-mile estimate Finance needs alongside the specs.
Normalize make and model names in columns A and B of the Fleet tab to API Ninjas format. For rows where column C is "Electric" or "BEV," fetch battery capacity, max charging power, and range from API Ninjas and fill columns D, E, and F. For non-EV rows, write "NOT EV" in column D. Flag any EV with range below 300 miles as "Range Caution" in column G. Calculate an estimated cost-per-mile assuming $0.13 per kWh and write into column H.
The pattern: enrichment, filtering, flagging, and a derived financial metric all in one instruction.
Try It
Get the 7-day free trial of SheetXAI and open any fleet inventory workbook, then ask SheetXAI to add EV specs using API Ninjas. The API Ninjas integration is included in every SheetXAI plan. See also how to decode VINs and add vehicle specs in Excel or the API Ninjas in Excel overview.