> For the complete documentation index, see [llms.txt](https://docs.verygoodsecurity.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.verygoodsecurity.com/vault/developer-tools/larky.md). # VGS Compute VGS Compute enables organizations to securely process, transform, and validate sensitive payloads in transit using Pythonic syntax. VGS Compute has been used extensively by enterprise customers to perform custom cryptographic operations, payload transformations, and policy enforcement in real time. VGS Compute combines programmability with isolation and security, enabling organizations to adapt to any internal or external integration requirement without compromising security, compliance, or code ownership. Powered by the VGS-maintained [starlarky runtime](https://github.com/verygoodsecurity/starlarky), VGS Compute allows you to inject programmable logic directly into your data flows, executing customer-written code on data as it passes through the VGS Secure Data proxies without ever exposing the underlying sensitive values. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.verygoodsecurity.com/vault/developer-tools/larky.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.