Private AI

Most companies are still asking how to use AI. The next question is how to use it privately. When your team plugs Claude or ChatGPT into the company's documents, where does that data go, and what can the AI labs do with it?In this episode of Web3 in Travel, Luca De Giglio explains why your data is worth far more to an AI lab than it ever was to Google, why a $20 subscription buys hundreds of dollars of inference, and what "we don't train on your data" really promises. He then walks through the options for private AI, from the most private to the least: local open-weight models on your own hardware, private APIs for open models, and Trusted Execution Environments (TEEs). For each, what it costs and what it actually protects.He closes with the strategy: route each task to the right model, decide which data must never leave the company, and accept that total privacy does not exist. You manage risk, you don't cancel it.IN THIS EPISODE• Why LLMs extract more value from your data t