Eidolon AI

What is Eidolon AI?

Eidolon AI is an open-source framework and enterprise agent server for building and operating generative AI applications. The Eidolon SDK provides a pluggable agent framework, while the Agent Server supplies a secure deployment environment. Developers can start from prebuilt agents, define their own with ordinary code or another agent framework, or configure them declaratively with YAML.

Agents can reference and communicate with other agents, use configurable RAG storage, and work with multiple models. Eidolon treats agents as stateless infrastructure services that deploy to Kubernetes and scale horizontally. Applications can consume agent actions through React components, a WebUI, REST APIs, a command-line interface, or Python and TypeScript clients.

How to Use Eidolon AI

1. Select a prebuilt agent or define a custom agent in code or declarative YAML.
2. Configure the model, system behavior, tools, RAG storage, and references to collaborating agents.
3. Run and test the agent in a local development environment.
4. Deploy the agent server through the organization's Kubernetes tools and pipeline.
5. Apply resource-access policies and scale stateless agent instances horizontally.
6. Integrate the deployed service through REST, WebUI, React components, CLI, Python, or TypeScript.

Core Features

• Enterprise agent server: Hosts agentic applications as secure, deployable services.
• Pluggable SDK: Supports custom implementations and agents defined with other frameworks.
• Declarative configuration: Defines simple or complex agents with YAML.
• Agent-to-agent communication: Connects specialist agents into collaborative systems.
• Configurable RAG: Adds retrieval storage and document search to applications.
• Kubernetes deployment: Uses existing cluster management and policy controls for production.
• Multiple clients: Exposes agents through REST, WebUI, CLI, React, Python, and TypeScript.

Use Cases

• Enterprise chatbots: Deploy multi-model conversational agents behind a standard service layer.
• RAG assistants: Search repositories, documentation, or private knowledge sources.
• Agent teams: Coordinate manager, engineering, quality, and other specialist agents.
• Embedded AI services: Add agent actions to a web product through APIs and React components.
• Governed deployment: Enforce Kubernetes policies so agents only reach required resources.

Pricing

Eidolon AI presents its framework and agent server as open source. The analyzed homepage does not list a commercial hosted plan or subscription price; infrastructure and model-provider costs depend on the user's deployment.

Frequently Asked Questions

Must agents be written only with Eidolon's SDK?

No. The website says developers can use vanilla code or another agent framework and deploy through the agent server.

Can Eidolon agents work together?

Yes. Agents can reference other agents and communicate as a multi-agent application.

How are agents deployed?

The documented production path deploys stateless agents to Kubernetes, where they can scale horizontally and inherit organizational policy controls.