AI Employee Types

Every AI Employee in Ema is powered by a GWE (Generative Workflow Engine) workflow. The workflow defines the logic. The type determines how the AI Employee interacts with end users -- its interface, input method, and output format.

When you create a new AI Employee, you select a type. This choice is permanent -- it cannot be changed after creation.

Available Types

Chat

Interface: Ema Webapp Chat at app.ema.co (or your custom domain).

Best for: Internal knowledge assistants, policy Q&A, compliance lookups, general-purpose AI assistants for employees.

How it works: Users interact through a conversational chat interface in the Ema web application. The AI Employee processes natural-language queries and returns text responses.

Key features:

• "Show Work" explanations for transparency into how the response was generated.
• Paragraph-level source citations with page numbers.
• Per-response feedback collection (thumbs up/down).
• Full conversation history.

Voice

Interface: Voice-based interaction via phone or voice channel.

Best for: Phone-based customer support, IVR replacement, voice-enabled assistants, outbound call campaigns.

How it works: The AI Employee handles voice conversations using speech-to-text and text-to-speech processing. Configuration includes voice settings (accent, speed, language), conversation behavior, call routing, data storage preferences, and phone number assignment for inbound and outbound calls.

Key features:

• Configurable voice characteristics (accent, speed, language).
• Conversation settings for behavior and tone.
• Call settings and routing configuration.
• VAD (Voice Activity Detection) settings for natural turn-taking.
• Phone number assignment for inbound and outbound calls.
• Data storage and feedback collection settings.

Dashboard

Interface: Structured tabular output (Agentic Dashboard).

Best for: Analytical tasks over large volumes of unstructured data. Bulk document processing. Data extraction and rule validation at scale.

How it works: Instead of conversational input/output, the Dashboard type processes structured inputs (rows of data or documents) and produces structured outputs in a tabular dashboard format. Each cell in the output is traceable to its source.

Key features:

• Bulk orchestration across many inputs.
• Per-cell source inspection.
• API and CSV export.
• Multiple input type support.
• Human-in-the-loop support with confidence scores.
• Filtered sub-dashboard views.

Document

Interface: Collaborative document editor (Ema Document Editor).

Best for: Long-form document generation (300+ pages), contracts, reports, policy documents.

How it works: An agentic collaborative editor that supports iterative generation and regeneration of document sections. Multiple users can collaborate on the same document.

Key features:

• Section-level collaboration.
• Version control and audit trail.
• Status management per section.
• Iterative regeneration.

Choosing the Right Type

API Access

All AI Employee types can be invoked via API, regardless of their primary interface. This allows you to integrate any AI Employee into custom UIs or backend workflows. See API Reference for details.

What Happens After You Choose

Once you select a type and create the AI Employee:

1. A GWE workflow is initialized with the appropriate trigger type (chat trigger, dashboard trigger, voice trigger, etc.).
2. Configuration widgets specific to the type appear on the AI Employee configuration page (e.g., voice settings for Voice, SDK config for Chatbot).
3. You can customize the workflow in the GWE canvas regardless of type -- the workflow logic is independent of the interface.

For a hands-on walkthrough of building your first AI Employee, see Create Your First AI Employee.