Academy

Learn to use AI in real team workflows, with shared context, clear boundaries and reviewable execution.

Start here

Begin with operating context. Then explore agents, workflows, deployment and open fair-code based on the decision in front of you.

Learning path

AI Foundations

Move from an isolated AI chat to a workspace where tasks, knowledge, data, decisions and approvals stay connected.

Start the learning path

Guides for real team workflows

Choose the question you need to answer now. Each guide covers examples, boundaries and a practical next step.

What is an AI workspace?

How tasks, knowledge, data, communication, workflows and AI agents work from one shared context.

Understand AI workspaces

AI agents in the enterprise

Which tasks agents can prepare and why sources, boundaries and human approvals belong in the workflow.

Evaluate AI agents

Build workflows with AI

Structure recurring work as a visible flow with ownership, data and defined approval points.

Read the workflow guide

Self-hosted or managed cloud?

Compare deployment models by control, infrastructure effort, integrations and operating responsibility.

Compare deployment models

Understand open fair-code

What inspectable code, self-hosting and licensed commercial use mean for teams adopting the workspace.

Read the fair-code guide

More resources

Documentation

Guidance for the product, setup and operations.

Open documentation

FAQ

Answers about the Hub, pricing, deployment and self-hosting.

Roadmap

What we are building now and what comes next.

GitHub

Code, issues and the public development state.

Release notes

New versions and changes to Pharen Hub.