In this video I show you how I basically cloned Apollo using a giant lead database and a little bit of Python. The whole point is simple: getting “old” leads isn’t enough—you can’t just cold email a random dump and expect it to work. You need a way to store it, search it fast, and then verify emails so you’re not nuking your domain. So I built a desktop-style prospecting engine where you can query a massive dataset by multiple data points, download results, and then run them through verification to get cold-email-ready leads. I walk through the exact setup: hosting the dataset on a DigitalOcean droplet that can handle huge storage, SSH’ing in, installing dependencies (yes, I copy-pasted a chunk from ChatGPT), uploading and unarchiving the files, then normalizing and chunking the CSVs so imports don’t fail. After that, I import everything into a database so it’s actually queryable, wait the painful 6–10 hours for the import, and then use a Python UI to search and export leads. The big takeaway: the “free leads” part is useless unless you build the workflow—storage, schema, search, and verification—so the output is usable for real campaigns.