Deploying Private LLMs Without Leaking Your Data
A practical guide to integrating large language models into your business while keeping sensitive data private and secure.
SASite AdministratorJul 2, 20261 min read
A practical guide to integrating large language models into your business while keeping sensitive data private and secure.
Generative AI offers enormous value — but only if it can be deployed without compromising data privacy. Here is how we approach secure LLM integration.
Retrieval-augmented generation lets models answer using your data without that data ever being used to train third-party models.
Input validation, output filtering, and PII redaction prevent both accidental leaks and prompt-injection attacks.
For the most sensitive workloads, open-weight models can run entirely within your own infrastructure.
Talk to our security experts about a tailored assessment, penetration test, or a custom software build for your organization.