The Scenario
You are a VC analyst and the deal team just updated the target list to 25 companies in the portfolio tracking sheet. The Monday partner meeting is in two hours. You need founding year, funding stage, estimated headcount, and key product for every company in column A — structured, accurate, not guessed from memory.
The bad version:
- Open a browser, search the first company, find the founding year on Crunchbase, copy it to column B, repeat for all 25 rows.
- Check LinkedIn for headcount estimates on each company, paste into column D, then cross-reference funding on PitchBook for column C.
- Spend 90 minutes doing research that is not analysis — and still not be sure every row is current.
The partners do not pay for data entry. They pay for the interpretation. An hour and a half of copy-paste is an hour and a half that is not pattern recognition.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads what is in the sheet, understands the layout, and through its built-in Parallel integration runs structured web research tasks for every row and writes the results back for you.
For every company name in column A of this sheet, use Parallel to research the founding year, latest funding stage, estimated headcount range, and primary product. Write the founding year into column B, funding stage into column C, headcount range into column D, and primary product into column E.
What You Get
- Column B populated with founding years across all 25 rows.
- Column C filled with funding stage labels (Seed, Series A, Series B, etc.) sourced from web research.
- Column D containing headcount range strings (e.g., 50-200 employees).
- Column E showing each company's primary product or service, as Parallel extracted it.
- Any row Parallel could not resolve left blank rather than guessed, so you know where to follow up.
What If the Data Is Not Quite Ready
Some company names in column A are abbreviated or use a brand alias
For every company name in column A, before running the Parallel research task, check whether the name looks like an abbreviation or alias. If it does, resolve it to the full legal company name using web lookup and put the resolved name into column F. Then run the Parallel research using column F as the input and write founding year, funding stage, headcount, and product into columns B through E.
The sheet has both a company name in column A and a known domain in column B — use both for better accuracy
Use both the company name in column A and the website domain in column B as inputs for the Parallel research task. For each row, submit both fields to Parallel and write the founding year into column C, funding stage into column D, headcount range into column E, and primary product into column F. Where the domain disambiguates a name collision, prefer the domain-matched result.
You only want to run Parallel on rows where column C is currently blank
For every row where column C is blank, use Parallel to research the company in column A. Write the founding year into column B, funding stage into column C, headcount range into column D, and primary product into column E. Skip rows where column C already has a value.
The sheet has inconsistent company names, some cells have trailing legal suffixes like Inc or Ltd, and you want clean output in one shot
For every company name in column A, strip any trailing legal suffixes (Inc, Ltd, LLC, Corp, GmbH) before submitting to Parallel. Run the research task and write the founding year into column B, funding stage into column C, headcount range into column D, and primary product into column E. If Parallel returns no result after stripping the suffix, retry with the full original name and note the retry in column F.
The pattern: name cleanup and research in one prompt — you describe the condition and the fallback, and SheetXAI handles the sequencing.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a company list in column A, then ask it to batch-research founding year, funding stage, headcount, and product using Parallel. You can also look at how to enrich a prospect list or return to the Parallel overview.