diff --git a/LICENSE b/LICENSE
index 93d6f98b..a47c5477 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,21 +1,28 @@
-MIT License
+GFX License
 
-Copyright (c) 2023 - 2025 Defence Science and Technology Laboratory UK (https://dstl.gov.uk)
+GFX Conditions
 
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
+These GFX conditions confirm the provision of the following artefacts as GFX by Defence Science and Technology
+Laboratory UK (DSTL) to QinetiQ Training and Simulation Ltd (QTSL) (and subcontractors engaged in activity on task by
+request to the QQ mailbox):
 
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
+- PrimAITE Overview
+- Access to PrimAITE & user instructions
+- Track 2 tech support
 
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+Suppliers will be required to sign up to the QTSL Collaborative Working Environment (CWE) SyOPs and fill out a User
+Access Request Form. Provided they have a minimum of Cyber Essentials, and the user has the required clearance, they
+will then be provided with credentials to access the site by QQ.
+
+DSTL mandate that any changes made to the PrimAITE source code be passed back to QTSL (during or on termination of the
+task) so that QQ can capture any potential enhancements to PrimAITE.
+
+This contains OFFICIAL information to be used to inform work on ARCD tasks (under SERAPIS).
+
+The material is supplied in confidence to QQ and their subcontractors under SERAPIS, and is issued to inform only those
+that need to know its contents in the course of their official duties whilst engaged in activities under the contract.
+The material consists of proprietary information which is the property of the Crown. The information contained within
+the material may constitute valuable technical information and be commercially sensitive in relation to third parties;
+therefore it may not be used or copied for any non-Governmental or commercial purpose without the prior written consent
+of DSTL. The material must be stored and protected appropriately.All material must be destroyed at the end of the task.
+Please note the contractual obligations relating to provision of these materials.
diff --git a/README.md b/README.md
index 326cc27e..d36c687e 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,38 @@
 # PrimAITE
 
-PrimAITE (Primary-level AI Training Environment) is a simulation environment for training AI under the ARCD programme.
+The ARCD Primary-level AI Training Environment (**PrimAITE**) provides an effective simulation capability for the purposes of training and evaluating AI in a cyber-defensive role. It incorporates the functionality required of a primary-level ARCD environment, which includes:
+
+- The ability to model a relevant platform / system context;
+
+- The ability to model key characteristics of a platform / system by representing connections, IP addresses, ports, traffic loading, operating systems, services and processes;
+
+- Operates at machine-speed to enable fast training cycles.
+
+PrimAITE presents the following features:
+
+- Highly configurable (via YAML files) to provide the means to model a variety of platform / system laydowns, mission profiles and adversarial attack scenarios;
+
+- A Reinforcement Learning (RL) reward function based on (a) the ability to counter the specific modelled adversarial cyber-attack, and (b) the ability to ensure mission success;
+
+- Provision of logging to support AI evaluation and metrics gathering;
+
+- Uses the concept of Information Exchange Requirements (IERs) to model background pattern of life, adversarial behaviour and mission data (on a sliding scale of criticality);
+
+- An Access Control List (ACL) function, mimicking the behaviour of a network firewall, is applied across the model, following standard ACL rule format (e.g. DENY/ALLOW, source IP address, destination IP address, protocol and port);
+
+- Application of IERs to the platform / system laydown adheres to the ACL ruleset;
+
+- Presents an OpenAI gym or RLLib interface to the environment, allowing integration with any OpenAI gym compliant defensive agents;
+
+- Full capture of discrete logs relating to agent training (full system state, agent actions taken, instantaneous and average reward for every step of every episode);
+
+- NetworkX provides laydown visualisation capability.
 
 ## Getting Started with PrimAITE
 
 ### 💫 Install & Run
 **PrimAITE** is designed to be OS-agnostic, and thus should work on most variations/distros of Linux, Windows, and MacOS.
-Currently, the PRimAITE wheel can only be installed from GitHub. This may change in the future with release to PyPi.
+Currently, the PrimAITE wheel can only be installed from GitHub. This may change in the future with release to PyPi.
 
 #### Windows (PowerShell)
 
diff --git a/pyproject.toml b/pyproject.toml
index c2c8076b..a33b2183 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,7 +10,7 @@ license = {file = "LICENSE"}
 requires-python = ">=3.8, <3.11"
 dynamic = ["version", "readme"]
 classifiers = [
-    "License :: OSI Approved :: MIT License",
+    "License :: GFX",
     "Development Status :: 5 - Production/Stable",
     "Operating System :: Microsoft :: Windows",
     "Operating System :: MacOS",