Agno

Agno suits developers assembling an agent platform on infrastructure they operate. Its SDK, runtime and control plane address different parts of that application. Memory, tools and evaluation help structure the work, while deployment still requires real models, data and permissions. A free runtime does not make the application's compute or model usage free.

A practical workflow

1. Choose a documented deployment template and configure permitted model access.
2. Build one agent with a narrowly scoped tool or knowledge source.
3. Inspect sessions and traces and add a relevant evaluation.
4. Test approvals and failure behavior before exposing the application to users.

Illustrative input

This example describes a task, not a tested output. Adjust the source material and settings to your own situation.

An internal support agent answers from approved documentation and requests approval before making any external change.

Result check: Verify source selection, tool arguments and the behavior when the answer is missing or a tool fails.

Access and alternatives

The open-source runtime and a local control-plane option are free; paid plans add live connections, seats and enterprise controls. Hosting, models, storage and connected services remain your responsibility. Check the distinction between a local free connection and a live managed control plane.

Choose another workflow when its emphasis fits better: CrewAI for a different agent orchestration framework; Dify for a more visual AI application workflow.