AutoGen

A workflow orchestration component of Microsoft's AutoGen framework for building directed agent workflows. It supports sequential and parallel steps, conditional branching, and loops.

AutoGPT is an open-source platform for building, deploying, and running AI agents that carry out complete workflows. Users can describe an outcome in plain English, or use its visual builder to drag, connect, branch, and inspect workflow blocks. Agents can run on demand, on schedules, or from event triggers, and the marketplace provides ready-made agents that can be added and customized. The hosted platform is a paid, usage-based service that manages infrastructure, model access, credentials, and updates; the self-hosted path is free of license fees but requires users to provide infrastructure and model API keys and maintain the deployment.

An agent-orchestration framework for Python that models complex, multilayered AI workflows as directed agent graphs. It manages context and tool calls, provides state checkpoints and persistence, and supports human-in-the-loop approval gates for production deployments. The framework is reported to allow existing agents to be exported/imported into IBM watsonx Orchestrate.

Agent-Native is an open-source TypeScript framework for building agentic applications with purpose-built user interfaces. Developers define each capability once as an action; the same action is used as an agent tool and called by the UI, with shared validation, permissions, implementation, data, and application state. Agents work through this shared action layer rather than clicking through the interface. Actions can also be exposed through HTTP, MCP, A2A, and a CLI. The framework includes agent chat, authentication and permissions, reusable skills and memory, scheduled or event-driven automations, multi-agent teams, and PostgreSQL support with PGlite for local development. It is distributed under the MIT license.

Hyperagent is an AI agent platform for assigning work to a fleet of agents that research, build, deliver and maintain outputs using an organization's data, tools and working style. Its agents operate through real browsers and shells, can search, code, make decisions and generate artifacts such as live websites, videos, presentations, documents and dashboards. Agents run in individual computing environments, expose their execution as it happens, and can learn new memories and skills over time. Work is delivered through Slack, email, Telegram, webhooks or scheduled runs, and agents are deployed and managed from a central command center.