Pragmatiks lets you define AI agents, models, tools, and cloud infrastructure as YAML resources. Apply them with a single command, and the platform handles provisioning, dependency resolution, and automatic change propagation.Documentation Index
Fetch the complete documentation index at: https://docs.pragmatiks.io/llms.txt
Use this file to discover all available pages before exploring further.
Get started
Deploy Your First AI Agent
Zero to a running AI agent in 20 minutes. Create a secret, configure a model, define an agent, and deploy it.
Build a Reactive AI Pipeline
Multi-agent teams with tools, knowledge bases, and reactive dependencies. 45 minutes.
Create a Custom Provider
Extend Pragmatiks with your own resource types. 60 minutes.
Why Pragmatiks
Reactive dependencies — Resources reference each other. When an upstream resource changes, dependents rebuild automatically. Swap a model, and every agent using it redeploys. Provider model — Providers encapsulate lifecycle logic for any service. The platform ships with providers for GCP, Kubernetes, and Agno. Build your own in Python. Real-time visibility — A web UI shows your dependency graph, resource states, and live event feeds. Watch changes propagate through your infrastructure.Learn more
How It Works
Understand the Pragmatiks model.
CLI Reference
Complete command reference.
Resource Catalog
Browse available providers and resource types.
Build a Provider
Create custom providers for any service.