How to Protect Sensitive Data by Running LLMs Locally with Ollama

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How to Protect Sensitive Data by Running LLMs Locally with Ollama
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Whenever engineers are building AI-powered applications, use of sensitive data is always a top priority. You don't want to send users' data to an external API that you don't control. For me, this happened when I was building FinanceGPT, which is my personal open-source project that helps me with my finances. This application lets you upload your bank statements, tax forms like 1099s, and so on, and then you can ask questions in plain English like, "How much did I spend on groceries this month?" or "What was my effective tax rate last year?" The problem is that answering these questions means sending all the sensitive transaction history, W-2s and income data to OpenAI or Anthropic or Google, which I was not comfortable with. Even after redacting PII data from these documents, I was not ok with the trade-off...

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