Pythagora’s Secure Spaces boost security for AI-driven apps
By Vriti Gothi

Pythagora, the AI-native development platform transforming how organisations build and deploy internal software, has launched Secure Spaces, a new security architecture designed to make privacy, isolation, and controlled access the default standard for AI-generated applications.
Secure Spaces introduces a foundational shift in how internal applications are conceived and protected. Instead of layering authentication, compliance, and permissioning at the end of a development cycle, every AI-generated application within Pythagora is now created inside a fully isolated Secure Space an environment architected to be private, secure, and contained from inception.
“Secure Spaces is not a feature. It’s a foundation,” said Zvonimir Sabljic, founder and CEO of Pythagora. “If we’re going to let AI build real internal tools, we have to stop bolting security on at the end. Every application needs to start with strong, opinionated defaults that protect data, users, and systems without slowing teams down.”
At the centre of this innovation is a reimagined runtime model. Each application is encapsulated in its own Secure Space, creating a dedicated security perimeter with no shared memory, no cross-application exposure, and no risk of credential leakage. Users can access an application only when explicitly granted permission, and all integrations stay sealed within the environment. From the moment an application is generated, it is private by default ensuring uncompromising protection even before the first line of logic is deployed.
The architecture also brings enhanced safety when connecting to internal APIs, databases, and sensitive production systems. Data remains local, credentials never leave the Secure Space, and teams can integrate confidently without concerns about spill-over into other tools or environments. By embedding security directly into the infrastructure, Pythagora enables developers to prioritise functionality, speed, and collaboration while maintaining robust controls automatically.
In an era defined by rapid expansion of AI-generated software, Secure Spaces represents more than an incremental update. It sets out a new operational framework for safeguarding applications built by machines rather than manually coded by humans. As enterprises accelerate toward AI-powered workflows, Secure Spaces removes the long-standing tension between agility and security. Developers gain immediate momentum, while platform and security teams retain enterprise-grade oversight without additional configuration or complexity.
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