The next question for enterprise AI isn’t just what AI can do. It’s where AI can run.
For teams operating under strict security policies, data residency requirements, and compliance regulations, adopting AI can come with a difficult trade off: unlock AI capabilities, or keep sensitive data within the boundaries of your own infrastructure.
Local LLM deployment changes that equation.
In this session, we’ll show how Qpilot can be deployed in a local environment, bringing AI powered test creation and execution closer to your applications, data, and security boundaries. You’ll see how enterprises can bring AI into their testing workflows while maintaining greater control over sensitive data and meeting the security requirements of regulated environments.
What you’ll walk away with ?
- A practical understanding of how local LLM deployment works and where it fits into an enterprise AI testing strategy.
- A live look at Qpilot running in a local setup, bringing AI powered test creation and execution into your own environment.
- How local deployment can help regulated teams keep sensitive application, test, and business data within their controlled infrastructure.
- How Qpilot’s local deployment can fit into existing testing workflows while keeping AI closer to the systems it needs to test.
