Testing AI-written code is one thing, testing it against real customer data raises the stakes. How do you give testing agents the access it needs while keeping that data isolated?
Lark built an AI test platform that maps a customer's product, writes end-to-end tests, and keeps running them as the code changes. That means testing environments with real user data and credentials in play.
Lark also needed to run Docker inside the sandbox itself to spin up a customer's own dev environment for testing.
@e2b's MicroVM isolation gave Lark strict security boundaries plus Docker-in-sandbox support, without having to build that isolation layer themselves.
"They're testing their live environments with real customer data or real API keys, and so everything has to be securely isolated. We don't want an agent in one sandbox to be peeping into another sandbox. It's crucial to the security of our product."
- Jack Brown, CEO, Lark
@uselark_ai
Read the full case study:
e2b.dev/customers/lark-case-…