XRisis Team Completes Platform Development Ahead of Validation Phase

Implementation Phase Completion

Nuwa has completed Phase 2 implementation of the XRisis humanitarian emergency training platform, successfully integrating all four planned CORTEX2 enabling technologies within Unity-based multi-user environments deployed on European cloud infrastructure. The platform now supports three distinct pilots addressing different emergency management cycle phases: arrival briefing with AI mentor Maud powered by CEA's Conversational Virtual Agent, collaborative alert and response strategy development employing Alcatel Lucent Enterprise's Rainbow CPaaS and interactive planning tools, and implementation simulation featuring AI-powered stakeholder negotiations requiring soft skills practice and adaptive communication. The development achievement represents substantial technical accomplishment given the complexity of coordinating multiple research-stage components from different consortium partners (DFKI, Alcatel Lucent Enterprise, CEA, Linagora) within coherent system architecture whilst maintaining usability for non-technical humanitarian professionals and reliability standards required for operational training delivery.

CORTEX2 Technology Integration Achievement

The platform successfully integrates Rainbow CPaaS providing secure real-time voice and video communication through Unity C# SDK native integration, enabling seamless audio spatial positioning in shared environments and conventional stereo audio during one-to-one calls without participant awareness of underlying technical complexity. DFKI's Video Call Alternative Appearance deploys via web-based emulator using MediaPipe and Ready Player Me, enabling facilitators and role-players to appear as avatars whilst privacy-aware communication capabilities mature toward deeper Rainbow integration. CEA's Conversational Virtual Agent powers multiple AI dialogue characters including Mentor Maud for arrival briefings and various stakeholder personalities for implementation scenarios, with knowledge grounding in Action Contre la Faim documentation ensuring responses reflect actual organisational procedures rather than generic emergency management principles. Linagora's summarisation agent integrates with Rainbow recording infrastructure, automatically generating PDF summary reports from training session transcripts supporting evidence-based post-exercise debrief conversations without requiring manual facilitator documentation efforts. This integration demonstrates successful progression from individual component feasibility testing to coordinated multi-component operational deployment achieving Technology Readiness Level 7 (system prototype demonstrated in intended operational environment).

Rehearsal Testing and Refinement

The March 2025 rehearsal workshop with Action Contre la Faim project team members provided comprehensive internal validation identifying interface improvements, workflow streamlining opportunities, and technical integration refinements implemented during final development sprint before engaging emergency roster personnel. Rehearsal feedback drove specific enhancements including navigation mechanism simplification reducing steps required for common tasks, addition of explicit task instructions clarifying participant expectations during each scenario phase, adjustment of AI avatar dialogue pacing enabling more natural conversational turn-taking, and reconfiguration of facilitator scenario management interfaces providing clearer observation windows and inject control mechanisms. The rehearsal process validated that internal testing with sympathetic users who understand platform development constraints generates different insights than validation with operational users evaluating finished systems against their training needs, with both feedback types serving essential but distinct purposes in development progression toward commercial deployment quality standards.

Validation Planning and Methodology

Preparation for May 2025 validation workshop with eight Action Contre la Faim emergency roster personnel is proceeding according to schedule established during September 2024 design workshop. The validation methodology combines System Usability Scale providing standardised usability measurement comparable to benchmark data, component-specific added value ratings assessing training effectiveness across five distinct capabilities, overall user satisfaction metrics, and qualitative debrief analysis capturing narrative feedback about strengths, limitations, and improvement priorities. Participant selection targets emergency response professionals with relevant deployment experience and prior simulation exercise familiarity, ensuring evaluation engages informed assessors capable of comparing XR capabilities against conventional training modalities rather than merely reacting to technological novelty. The validation approach satisfies dual requirements: demonstrating effective CORTEX2 enabling technology integration meeting consortium evaluation criteria, and assessing humanitarian training value informing Action Contre la Faim operational deployment decisions and Nuwa commercial platform development priorities.

Strategic Positioning for Commercial Transition

Completing platform development on schedule with comprehensive CORTEX2 technology integration positions Nuwa for confident validation knowing that technical capabilities have achieved sufficient maturity to demonstrate intended functionality rather than struggling with integration issues that would undermine credibility during critical evaluation events. The timeline progression from requirements gathering through design specification to implementation completion demonstrates disciplined project management and effective collaboration between technical development, domain expertise, and training design perspectives. Validation outcomes will directly inform commercial platform evolution strategy, with quantitative metrics and qualitative feedback guiding resource allocation decisions about which capabilities merit continued investment versus which require reconsideration or elimination based on demonstrated training value rather than speculative assumptions about technological benefits.