FastAgency vs Windmill

Side-by-side comparison of two AI agent tools

FastAgencyopen-source

The fastest way to bring multi-agent workflows to production.

Windmillopen-source

Open-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs. Fastest workflow engine (13x vs Airflow). Open-source alternative to Retool and Temporal.

Metrics

FastAgencyWindmill
Stars54818.1k
Star velocity /mo2.5668449197860963317.80748663101605
Commits (90d)01.2k
Releases (6m)010
Overall score0.243869536052831430.8726503315063926

Pros

  • +Unified interface for deploying AG2 workflows to production with minimal code changes
  • +Supports both web chat applications and REST API services from the same codebase
  • +Built-in scaling capabilities with distributed architecture and message broker coordination
  • +Multi-language support with automatic UI generation from scripts in Python, TypeScript, Go, Bash, SQL, and more
  • +High performance workflow engine claiming 13x faster execution than Airflow
  • +Self-hostable open-source solution with AGPLv3 license providing full control and customization

Cons

  • -Dependent on AG2 framework, limiting flexibility to other agent frameworks
  • -Relatively small community with 532 GitHub stars compared to major frameworks
  • -Limited documentation available in the provided materials for advanced features
  • -AGPLv3 license may restrict some commercial use cases and require careful compliance consideration
  • -Being a comprehensive platform may introduce complexity for simple automation tasks
  • -Self-hosting requires infrastructure management and maintenance overhead

Use Cases

  • •Deploying AG2 multi-agent chatbots as web applications for customer service or support
  • •Creating REST API services that expose agent workflows for integration with existing systems
  • •Building scalable distributed agent systems that coordinate across multiple servers or datacenters
  • •Building internal APIs and webhooks from existing scripts without additional infrastructure
  • •Creating automated workflows for background jobs and data processing pipelines
  • •Developing low-code internal applications with custom UIs for non-technical team members