AgentRunner

• Visual workflow builder with a drag-and-drop node interface
• Multi-model support including GPT, Claude, Gemini, and local LLMs
• Create fully autonomous task-driven agents
• Version control for agent updates and experimentation
• Real-time logs and execution history for better debugging
• API endpoints to deploy and integrate agents into applications
• Agent memory for long-term context handling
• Conditional logic and branching for complex automations
• Team collaboration with roles and shared workspaces
• Secure cloud environment with encrypted key management

AgentRunner is a visual AI workflow builder designed to help developers and teams create, test, manage, and deploy AI agents. The platform provides a visual environment where users can construct AI workflows instead of building every component entirely through traditional code. It is aimed primarily at developers and teams working on AI-powered applications, automation, chatbots, and agent-based workflows.

The platform provides a visual Agent Editor for creating and modifying AI agents. Users can organize prompts and processing steps into workflows, making it easier to experiment with different approaches and refine how an agent handles a particular task. Prompt chaining allows multiple AI operations to be connected together so that the output of one step can be used by another part of the workflow.

AgentRunner also includes tools for understanding how agents operate. Detailed run logs allow users to inspect individual executions, while node history provides visibility into the steps completed during an agent run. These capabilities can be useful when testing workflows, identifying problems, and refining prompts.

For development teams, AgentRunner includes version control features for managing changes to AI applications. Agents can also be executed through an API, allowing developers to connect workflows with external applications and services. Workspace functionality provides different user roles, including owners, developers, and operators, which can help teams manage access to AI projects.

AgentRunner is particularly suited to developers, AI application builders, automation teams, and organizations experimenting with custom AI agents. Its visual workflow approach can reduce the need to construct every agent process manually and provides a more structured environment for testing and deployment.

AgentRunner has been offered in beta with free access. Current paid plan pricing is not publicly disclosed. The platform’s focus on visual workflow construction, prompt engineering, execution monitoring, version control, and API access makes it suitable for teams developing customized AI applications rather than users seeking a simple conversational chatbot.

Overall, AgentRunner provides a development environment for turning prompts and AI models into structured workflows that can be tested, managed, and integrated into broader software applications.

Frequently Asked Questions

What is AgentRunner used for?

AgentRunner is used to build, test, manage, and deploy AI agents and AI-powered workflows. It is designed primarily for developers and teams creating customized AI applications and automation systems.

Is AgentRunner free to use?

AgentRunner has offered free beta access for users building and testing AI agents. Current paid plan pricing is not publicly disclosed, so users should check the platform for the latest commercial terms.

How does AgentRunner work?

AgentRunner works through a visual workflow interface where users connect prompts, AI operations, and workflow steps to create an agent. The resulting workflow can be tested through agent runs, reviewed through logs, and accessed through an API.

Who is AgentRunner designed for?

AgentRunner is designed mainly for developers, AI engineers, automation teams, and organizations building custom AI applications. Its visual editor and API capabilities are intended for users who need more control than a standard AI chatbot provides.

Can AgentRunner connect AI workflows to other applications?

Yes, AgentRunner provides API access for running agents from external applications. This allows developers to incorporate AgentRunner workflows into software products, automation systems, and other development environments.

What makes AgentRunner different from a normal AI chatbot?

AgentRunner focuses on building and managing AI workflows rather than simply providing a conversational interface. Features such as visual agent construction, prompt chaining, execution logs, version control, and API access support the development of customized AI applications.

Does AgentRunner provide workflow execution logs?

Yes, AgentRunner provides detailed run logs that allow users to inspect how an agent performed during execution. Node history can also show the individual workflow steps completed during a run.

Can AgentRunner be used to deploy AI agents?

Yes, AgentRunner is designed to support the development and deployment of AI agents and workflows. Developers can create agents visually, test their behavior, manage versions, and run them through API access.

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