Cyber REX Agent

Purpose

Cyber REX Agent is designed to support lessons-learned and After Action Review guidance using only facts present in the conversation history. Its purpose is to help structure review guidance without adding unsupported assumptions or information not explicitly provided.

Primary users

The primary user is not specified. Based on the provided team information, the agent is associated with CYB and is intended for cross-industry use.

Where it fits (process/stage/trigger)

Cyber REX Agent fits into lessons-learned and After Action Review activities after relevant facts have been captured in the conversation history. It is triggered when users need guidance based only on the information already present in the exchange.

Key capabilities / workflow

Cyber REX Agent reviews the conversation history, checks whether facts are available, extracts relevant lessons-learned elements, validates that guidance is supported by the provided facts, and delivers After Action Review guidance while flagging gaps where information is not specified.

Inputs

Inputs are not specified. The agent must use only facts present in the conversation history; the provided dataset context includes open market data, anonymised data, internal/private Sia data, and client data.

Outputs / Deliverables

Outputs are not specified. The stated use case is lessons-learned and After Action Review guidance, so deliverables should remain limited to guidance supported by facts present in the conversation history.

Value

Cyber REX Agent helps users produce fact-grounded lessons-learned and After Action Review guidance while reducing the risk of unsupported conclusions. Its value lies in keeping review outputs aligned with explicitly provided information and identifying areas where details are missing.