Firmographics, location, web context, and social & ad presence. One at a time, or a whole list. For you and your AI.
Paste any of these three files straight in, unchanged — the box below reads LinkedIn's own headers automatically: Connections.csv (your contacts and where they work), Positions.csv (your own work history), or Company Follows.csv (companies you follow).
Heads up on Connections.csv specifically: tested this against a real "Get a copy of your data" download (2026-08-14) and the default/"Basic" archive did not include it — LinkedIn only bundles Connections.csv if you request it as a separate item under "Want something in particular?", and it can arrive by email later rather than in the instant download. LinkedIn's own export instructions Positions.csv and Company Follows.csv, by contrast, are both in the default archive and both work here today.
We only enrich the Company column. Names, titles, and dates are shown exactly as LinkedIn gave them to you, never looked up, never sent to an enrichment engine. Never use a scraper or a "LinkedIn automation" tool to build any of these files: LinkedIn's terms prohibit automated collection and actively enforce it (LinkedIn sued the scraping service Nubela/Proxycurl in 2026) — the official export is free, native to every account, and the only source this page is designed around.
Same choice as single-company mode — pick once, it applies to every company you ticked in step 2. The price below multiplies by how many you selected, not by the size of the file you imported.
Don't hunt for the right field or graph — just ask. Your enriched companies (sector, size, funding, HQ, and how many of your contacts are at each) go to the model named above, which answers in plain English. Company-level only — your contacts' names never leave your file. Two real answers over this exact network, already run and paid, are below.
A form fill carries a name and an email domain. One call turns that into an account record a router can act on.
Run the whole list through company profile once, keep the fields your scoring model actually uses, drop the rest.
Location & property turns an address into an aerial view and a building read, not just a pin on a map.
Web context pulls what a company's own site currently says about itself, alongside the firmographic record.
Paste a target-account list or a LinkedIn Sales Navigator export, and enrich the whole thing in one run instead of one row at a time.
Ad-library and social-presence data tells you whether an account is actively spending on demand gen before you build a competing pitch.