Overview

Frontierz delivers live training and onboarding through configurable AI Fellows. Sessions are voice-based and run in real time, similar to a video call.

Frontierz is built on two core components:

• AI Fellows. Configurable conversational AI with a defined persona, purpose, Knowledge Base, and set of Connectors. Users speak to an AI Fellow and receive responses in real time. AI Fellows can also be created as AI Simulations, where the AI Fellow plays a defined role for practice and assessment.
• Learning Paths. Structured programs composed of sequential sessions and objectives. An AI Fellow runs each session and confirms that its objectives are met before the next session unlocks.

AI Fellows and Learning Paths can be deployed independently or in combination. A standalone AI Fellow on a public link is sufficient for a focused coaching tool. A Learning Path is recommended when progress tracking across multiple sessions is required.

Frontierz is most effective for use cases where the primary value is in a conversation, such as coaching, simulation, interview rehearsal, onboarding, or competency assessment. It is not designed for passive content such as videos, documents, or multiple-choice assessments.

Frontierz is not a learning management system (LMS) and is not a general-purpose chatbot. It can operate alongside an existing LMS, and a Learning Path can write completion data back to it through a custom Connector. AI Fellows are voice-first by default. When an admin enables text chat mode, the same AI Fellow can also be used by typing. AI Fellows can interpret a shared screen and interact with external systems through Connectors.

Administrator capabilities

From Frontierz Studio, Admin users can:

• Build and edit Learning Paths. Define sessions, write objectives, enroll users, upload reference material for the AI Fellow, or generate a full draft Learning Path with Build with AI.
• Build and edit AI Fellows. Configure the persona, voice, language, instructions, knowledge, and Connectors.
• Create AI Simulations from a guided form when the goal is role-play practice rather than a general AI Fellow.
• Set each AI Fellow's visibility (Public, Private, or Disabled) and manage the access list of any Private AI Fellow.
• Manage Connectors. These are the integrations that allow an AI Fellow to act during a conversation, such as screen sharing, calendar invitations, or calls into customer systems.
• Enable or disable built-in capabilities (Screen Share, Schedule Next Session) on the AI Fellows and Learning Paths where they apply.
• Invite Admin users and assign which Learning Paths and AI Fellows each Manager oversees. See Roles and permissions.
• Open a single user detail page for Users, Managers, and Full Admins to review activity, platform usage, account details, and workspace permissions. See User detail.
• Generate a Learning Path report from the analytics dashboard, then print it or download it as PDF or DOCX.
• Generate an AI Fellow report for a single AI Fellow from its conversations, then print or export it.
• Import a SCORM package as a new Learning Path, or add one as a session in an existing Learning Path.
• Track usage, identify users who are progressing or stuck, review AI Fellow conversations, inspect every Connector execution, and open the AI Fellow edit history.
• Use View as User to confirm what a User sees without changing their own login.

The number of AI Fellows and Learning Paths per company is not capped. Each AI Fellow can hold up to 20 documents in its Knowledge Base.

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