Hi everyone,
I’ve been working on integrating LLM APIs into applications, and one challenge keeps coming up: handling sensitive data (PII) safely.
In many real-world cases, user input or internal data can include things like:
– names
– emails
– phone numbers
– financial or account-related info
Before sending anything to an AI model, this raises a few questions:
– Are you anonymizing or redacting data before sending it to LLMs?
– What tools or approaches are you using (regex, NLP models, middleware, etc.)?
– How do you balance data privacy with maintaining useful context for the model?
– Any lessons learned from production deployments?
Curious how others in IT / enterprise environments are approaching this.
Would love to hear your experiences.