Introduction
Praxis is an AI Workforce Platform - build specialized AI teammates through conversation, not configuration.
Build Your AI Workforce
Instead of clicking through menus and writing config files, you describe what you need. Praxis handles the rest.
Everything Through Conversation
You: "I need an agent that monitors our payment service"
Praxis: "I'll create a Payment Monitor agent. What should it track?
- Pod health and restarts?
- Error rates and latency?
- Database connections?"
You: "All of those. Connect it to our Prometheus too."
Praxis: "Done! Your Payment Monitor has:
✓ kubectl access to payment namespace
✓ Prometheus queries for metrics
Try: 'How is the payment service doing?'"
This is how you "hire" your AI workforce - through conversation.
What You Can Build
Agents
Specialized AI workers for specific domains. Each has expertise, tools, and skills configured for their role.
Skills
Knowledge packages agents load on demand - step-by-step workflows for tasks like debugging deployments or analyzing logs.
MCPs (Tools)
Connections to external services - Kubernetes, Terraform, Git, cloud APIs, and your own tools.
Tasks
Reusable operations you define once and run whenever needed - health checks, analysis workflows, deployment procedures.
Extend Through Conversation
| What You Need | What You Say |
|---|---|
| New specialist | "Create an agent for monitoring our APIs" |
| New capability | "My agent needs access to Prometheus" |
| New workflow | "Create a task for our daily health check" |
| Share with team | "Make this available to everyone" |
Praxis configures everything - you just describe what you need.
Getting Started
- Quick Start - Your first conversation
- Connect Tools - Add Kubernetes, Git, and more
- Hire an Agent - Create your first specialist
Learn the Concepts
- AI Workforce - The workforce model
- Agents & Subagents - How agents delegate work
- Skills - Reusable knowledge packages
- MCPs - Tool connections
- Tasks - Reusable operations