Enrich any CSV with AI and web search
The generic case. If you can describe the column you want in a sentence, and the answer exists on the public web, this works.
Updated August 2026
What goes in, what comes out
Input
- Any identifying column
Output
- Whatever you describe
The prompt
Paste this into the description field, or write your own version of it.
Describe the fields you want in plain English. OpenClay converts your description into a per-row prompt with your columns substituted in, and asks the model to return strict JSON.
Why this works
Nothing about the tool is specific to companies or sales. Every row is an independent prompt with that row's values substituted in, so the same machinery works for products, countries, papers, properties or anything else with a public footprint.
Getting the best results
Anything with a public footprint is fair game. The clearer your column names, the better the results: specific questions produce specific answers, and the five-row test shows you the quality before you commit to a batch.
What it costs
On Gemini 3 Flash, a typical row of this shape costs about <$0.01, so roughly $0.55 per thousand rows, paid directly to Google. OpenClay adds nothing.
The tool shows an exact figure after a five-row test, before you commit to the batch. See all models and pricing.
Step by step
- 1Upload the file. CSV, XLS or XLSX up to 10 MB, parsed entirely in your browser.
- 2Choose input columns. Pick the columns that identify the thing being researched.
- 3Name your output columns. Each becomes a new column in the downloaded file.
- 4Test, run, download. Five rows first for an exact cost, then the full batch.
No account, no card, no platform fee.
Bring your own API key and pay the model provider directly.
Start enriching, freeOther use cases
- Enrich a company list with AI: Turn a column of company names into leadership, funding, headcount and positioning, researched from the live web one row at a time.
- Enrich a lead list without paying for Clay: Export raw prospects from Apollo, lemlist or LinkedIn, enrich them with live research, and pipe them back into your sequencer.
- Build a competitor matrix with AI: Give it a column of competitors and get pricing, positioning, target segment and differentiators back as structured columns.
- Enrich a list of universities: Rankings, acceptance rates, tuition and programme details for hundreds of institutions, without copying from a dozen tabs.
- Track hiring signals across companies: Open roles, the functions being hired, and the careers page URL: a decent proxy for where a company is investing.