> Source: https://builder-docs.ema.ai/emafusion/setup
> Title: EmaFusion Setup & Configuration

# EmaFusion Setup & Configuration

EmaFusion can be configured at two levels: the **AI Employee level** (applies to all agents within the AI Employee) and the **individual agent level** (overrides the AI Employee default for a specific agent).

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## AI Employee-Level Configuration

### Step 1 -- Open Configuration

1.  Go to your **AI Employee Dashboard**.
2.  Select the AI Employee you want to configure.
3.  Click **Configuration** in the left-hand menu.

### Step 2 -- Choose a Model Setting

You will see three configuration options:

#### Option 1: Use All Available Large Language Models (Recommended)

EmaFusion selects from 40+ models automatically. You can further select how to optimize model selection:

Optimization Mode

Behavior

**Balanced / Auto** (default)

Prioritize models based on task type, optimizing between accuracy, latency, and cost.

**Fastest**

Prioritize models with the lowest response time.

**Cheapest**

Prioritize models with the lowest cost.

**Most Accurate**

Prioritize models with the highest accuracy for the task.

#### Option 2: Limit to Specific Models

Choose which models (e.g., GPT-5.4, Claude, Gemini) EmaFusion can use from the model picker dropdown. EmaFusion will only select among the specified models.

-   If you select two or more models, you can further select an optimization mode (Balanced, Fastest, Cheapest, Most Accurate).
-   The model picker dropdown shows only models that are compatible with the agents in your workflow. If agents have not had their model configuration overridden, the dropdown displays the union of eligible models across all such agents and disables the rest. See [Model and Agent Capabilities](#model-and-agent-capabilities) below for details.
-   **Trade-off:** Restricting models may reduce overall performance.

#### Option 3: Use Your Custom Model (BYOM)

Enter your **API URL** and **API Key** for your custom model. This connects your private OpenAI, Gemini, or internal LLM instance.

**Important:** Currently, only one custom model can be set per AI Employee.

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## Agent-Level Configuration

Each agent inside an AI Employee can have its own EmaFusion configuration.

### Steps

1.  Go to your AI Employee and open the **Agents** tab.
2.  Select the agent you want to configure.
3.  Click **Advanced Settings** and then **EmaFusion Configuration**.

### Behavior

-   By default, all newly added agents **inherit** the model configuration from the AI Employee.
-   You can override the default by selecting the **Override default configuration** toggle and changing settings.
-   **Custom models (BYOM) are not supported at agent level.** If a custom model is set at the AI Employee level, all agents will use it.
-   For the "Limit to the following Large Language Models" option at agent level, only models that have the capabilities needed by that specific agent will be enabled in the dropdown.

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## Model and Agent Capabilities

Under the hood, every agent and model has a predefined set of capabilities:

-   **Model capabilities** describe what the model can do (e.g., text generation, structured output).
-   **Agent capabilities** describe what model capabilities the agent needs.

When you select "Limit to the following Large Language Models" at either the agent or AI Employee level, a filtering mechanism enables only models that are eligible for the agent or AI Employee. This prevents runtime issues where an agent attempts to use a model that lacks a required capability.

### Capability Mismatch Errors

If an agent inherits its model configuration from the AI Employee, and an ineligible model has been set at the AI Employee level, an error will be displayed for that agent.

**To resolve the error:**

1.  Click **Override default configuration** on the agent.
2.  Select one of the eligible models from the dropdown, **or**
3.  Select **Use all available Large Language Models**, **or**
4.  Specify a custom model if you have one.

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## Best Practices

-   Start with **Use all available LLMs** (the default) and the **Balanced** optimization mode. This gives EmaFusion the widest selection for optimal routing.
-   Only restrict models when you have a specific requirement (compliance, cost ceiling, latency SLA).
-   Use **agent-level overrides** sparingly -- for example, when a particular agent needs a model with specialized capabilities that differs from the AI Employee default.
-   When using BYOM, ensure your custom model's API is reliable and low-latency, as it becomes the sole model for the AI Employee.
-   If you need different models for different agents, override at the agent level rather than restricting the AI Employee-level configuration. This preserves EmaFusion's flexibility for agents that do not require a specific model.

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## Related Pages

-   [How EmaFusion Works](/legacy-docs/emafusion/how-it-works) -- Architecture, routing, and benefits.
-   [Troubleshooting & Support](/legacy-docs/troubleshooting/common-failures) -- Common errors and how to address them.