Copy-paste formulas for VC deal sourcing in Google Sheets
Paste a formula into row 2, test it on a few rows, then drag down to run the workflow across your spreadsheet.
Company / founder research
A: company · B: source notes/links · C: thesis · D: stage focus
=GPT("Research this company for VC sourcing: " & A2 & ". Source notes: " & B2 & ". Our thesis: " & C2 & ". Stage focus: " & D2 & ". Return a concise summary, sector, what they do, traction signals if stated, missing data, and one next action. Mark any funding/traction claim as unverified unless clearly sourced.")
Thesis fit score
A: company · B: thesis criteria · C: source text
=GPT("Score this company 1-5 for thesis fit. Company: " & A2 & ". Thesis criteria: " & B2 & ". Source text: " & C2 & ". Return score, reason, sector/stage read, confidence, and what to verify manually.")
Founder outreach angle
A: founder · B: signal · C: what we offer · D: tone
=GPT("Write a specific, respectful outreach opener to founder " & A2 & " based on this signal: " & B2 & ". What we offer: " & C2 & ". Tone: " & D2 & ". Keep it factual, non-presumptuous, and under 70 words.")
QA missing-data flag
A: AI output · B: source text · C: required fields
=GPT("QA this output: " & A2 & ". Source text: " & B2 & ". Required fields: " & C2 & ". Return missing data, risky assumptions, unsupported claims, and pass/review/fail.")
Short answer
A Clay alternative for VC deal sourcing in Google Sheets is a spreadsheet-native way to enrich and score sourcing pipelines without a heavy external stack. Instead of researching companies one at a time, GPT for Sheets runs prompts across a full table of companies, founders, sectors, and stage signals, and produces research summaries, thesis-fit scores, and shortlisting rationale in adjacent columns.
Fastest path: Install GPT for Sheets → add your source columns → paste a formula from the formula section → review 10 rows → fill down the sheet.
This page is for early-stage VC platform and sourcing teams, scouts, angel syndicates, and accelerator teams who keep sourcing lists in spreadsheets and want faster, reviewable research at scale.
Workflow
A practical deal-sourcing sheet usually has these columns:
| Column | What to put there | Why it matters |
|---|---|---|
| A | Company name | Stable row anchor for each prospect |
| B | Source notes or links: site, deck, press, directory | Keeps AI grounded in inspectable evidence |
| C | Sector or category | Sharpens thesis fit |
| D | Stage focus or thesis criteria | Aligns the row to your mandate |
| E | AI research summary | First useful interpretation of the row |
| F | Thesis fit score | Sorts the pipeline for review |
| G | Shortlist note or next action | Turns research into a decision |
| H | QA flag | Marks unverified funding/traction claims |
Step-by-step setup
- Start with 10 representative companies before filling down hundreds of rows.
- Keep raw source fields unchanged in columns A-D so you can audit the AI.
- Use one formula to create a research summary, then inspect weak rows.
- Add constraints: max length, required format, and explicit instructions to mark funding/traction claims as unverified.
- Add a QA formula that flags missing facts and unsupported assumptions.
- Fill down once the prompt works on sample rows.
Why sourcing teams compare this with Clay
Clay is a capable enrichment platform, but many investment teams do not want a separate GTM workspace for sourcing. GPT for Sheets is positioned for teams that already share sourcing lists in Google Sheets and want a spreadsheet-native way to turn company and founder rows into research, fit scores, and shortlists. It is not affiliated with Clay; Clay and other third-party product names are trademarks of their respective owners, and comparisons here are factual and non-defamatory.
Use cases
- Pipeline enrichment: turn raw company lists into reviewable summaries with sector and stage reads.
- Thesis scoring: label companies by fit to your mandate before partner review.
- Shortlisting: generate rationale and next actions for each candidate.
- List cleanup: normalize exports from directories and databases into consistent fields.
- QA: flag rows where funding or traction claims are unverified.
Best for / not best for
Best for: sourcing and platform teams who keep pipelines in Google Sheets and want faster, reviewable AI research across many companies.
Not best for: teams that need a licensed proprietary funding database, investment decisions without human review, or a fully managed data platform outside Sheets. This page is not investment advice.
The strongest use case is when you already have a sourcing list and need structured AI output. If your core need is buying a proprietary database, use GPT for Sheets as the research, cleanup, and shortlisting layer after export.
Internal links and next workflows
- GPT for Sheets product page
- GPT for Sheets pricing
- Account research automation
- Clay alternative for SaaS founders
- AI lead scoring formulas
- Upgrade GPT for Sheets
Safety, compliance, and data quality
AI output should be treated as a draft, and this page is not financial or investment advice. Treat funding, valuation, and traction claims as unverified until sourced, keep source columns visible, store links, and review important rows before acting. For founder outreach, follow consent and local compliance rules.
Frequently Asked Questions
What is the fastest way to start deal sourcing in Sheets?
Install GPT for Sheets, add columns for the company, source links, sector, and stage, paste one formula into row 2, review the output, then fill it down once it works on sample rows.
Is this really a Clay alternative for VC sourcing?
For spreadsheet-first teams, yes: GPT for Sheets provides Clay-style research, scoring, and shortlisting directly in Google Sheets. It is not affiliated with Clay and does not replace every proprietary data source.
Can it verify funding or traction?
No. It can summarize what your source text states and flag claims, but funding and traction figures must be treated as unverified until you confirm them from a reliable source.
Should I trust every AI output automatically?
No. Treat output as a structured draft and use QA columns to flag missing evidence, unsupported claims, and rows that need manual research.
Start deal sourcing in Google Sheets
If your team already works in spreadsheets, install GPT for Sheets and run these formulas where your sourcing pipeline already lives.
Install GPT for Sheets or compare plans to turn sourcing rows into reviewed research, fit scores, and shortlists.