Prototype speed.
Production infrastructure.

A plain-language summary of the app: what it does, how it is structured, what it touches. Generated on deploy and kept current, it is the front page of the app for anyone who did not build it. Scroll the real thing below.

A generated presentation of the app: what it does, who it is for, the problem it solves. Ready to share with a team or a stakeholder, without anyone building slides. Page through the slides below.

A security and governance assessment of the app, grounded in the deployed code and regenerated on every deploy. It covers overall posture, access model, findings with file-and-line citations, a data-flow diagram, and a filled CAIQ attestation. Read the findings below.

A living roadmap for the app. As it runs, the platform adds improvements and next steps to it automatically.

Usage across the app: users, sessions, and which methods get used, without any tracking code added by hand.

Every app is also a documented HTTP API; its methods are callable as endpoints. Browse the endpoints below.

Every app is also an MCP server, so its methods are available as tools to any AI agent that speaks the protocol. Inspect the tools below.

Every app also gets an email address: inbound mail can trigger its methods.

An immutable, exportable record of who did what, across the workspace and inside the app itself, down to individual method calls, in OCSF for any SIEM.

Every app is written against one SDK that carries 330+ AI models across every modality, an agent runtime, and 1,000+ integrations, with no keys to manage. Bring your own keys, route models, and govern model usage across the organization.

Choose where a workspace stores its data at rest, across the United States, European Union, Canada, and Australia, with more regions coming. New data follows the choice immediately, the region is changeable at any time, and an opt-in migration relocates existing data.