Open-source durable execution platform for building reliable distributed workflows and long-running processes.

Asset-oriented data orchestration platform for building, testing, and monitoring data pipelines in production.

Microsoft Research's system connecting LLMs to 1000+ Hugging Face models for multi-modal task planning and execution.

Hugging Face's minimalist library for building agents that write and execute Python code as their primary action.

Microsoft's open-source toolkit for building, evaluating, and deploying high-quality LLM applications end-to-end.

Build stateful, multi-actor agent workflows as directed graphs — cycles, branching, human-in-the-loop, and persistent state built in.

Role-based multi-agent orchestration framework — define a crew of AI agents with distinct roles, tools, and goals that collaborate autonomously.

Platform for building stateful AI agents with advanced memory that can learn and self-improve over time.

Microsoft's multi-agent conversation framework — build teams of LLM agents that converse, code, debate, and solve complex tasks together.

Declarative YAML-based orchestration platform with 1500+ plugins for automating data, AI, and infrastructure workflows.

Kubernetes-native ML and data workflow orchestrator with first-class type safety, reproducibility, and multi-cloud support.