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AirADAPT TACFI

AFWERX · AFWERX TACFI · AFWERX

AI-Readiness Score
14/25
Pathway Speed
4/5
Timeline Realism
3/5
Problem Framing
3/5
AI / ML Fit
3/5
Award + Transition
1/5

Award

$750,000
Award ceiling
Design Interactive, LLC
Awardee
Posted July 15, 2024

Description

The United States Department of the Air Force (DAF) is strategically pursuing advanced technology solutions to enhance existing training systems and prepare its warfighters for high-end combat. This initiative will create large-scale, integrated networks of simulation tools to support forces training collaboratively across individuals, crews, and units. Global Strike Command (GSC) is strategically assessing technologies and instructional methodologies that can transform training and solve specific GSC command needs through the Air Refueling Challenge and the Advanced Training Challenge. An opportunity exists to extend the utility of training technologies resulting from these design challenges by providing effective and robust performance analytics that can drive personalized and adaptive instruction. This solution would need to integrate with emerging AR/VR and simulation-based training systems to provide a sustainable and extensible assessment and analytics technology to the USAF. The USAF will benefit from a training assessment tool with the capacity to evaluate individual and team proficiency across multiple performance aspects.Design Interactive, Inc. (DI) is developing AirADAPT, a performance analytics and adaptive instruction engine that will integrate data from multiple sources for data driven adaptations during and following training. AirADAPT includes: (1) automated performance assessment through consumption and analysis of real-time data from external training technologies, (2) an instructor dashboard for effective performance monitoring and instructor intervention for individuals and/or teams, (3) personalized coaching, feedback, and integrated auto-adaptive training triggers, and (4) the potential for advanced automated assessments that leverages AI to improve adaptivity and personalization in future enhancements.The proposed effort seeks to expand on the Phase II AirADAPT prototype, which provides adaptive training and assessment within USAF operational environments, specifically in the domain of air refueling. The focus will be on supporting large scale adaptability through expansion to new rating scales and training use cases to enable broader application across AFGSC training environments. Proposed work also includes the development of analytics and leaderboards and refining the adaptive performance algorithm to support automated assessment and enterprise level performance tracking. The scope includes research into interoperability with virtual trainer technologies, along with documenting associated challenges along with other requirements for ATO in support of transitioning to a GSC training environment. The prototype will provide measurable performance on the utility of the approach and AirADAPT application to GSC training challenges.

Score Rationale

TACFI is a genuine fast-track AFWERX instrument that scores well on pathway speed, but the $750K ceiling with no explicit production transition mechanism beyond vague ATO documentation pulls the award/transition score to 1 — this is a prototype extension, not a funded path to program-of-record. The AI/ML fit is real but secondary: the core deliverable is a performance analytics and adaptive instruction engine where AI improves personalization at the margins, while the heavier lift is systems integration with AR/VR and simulation platforms and interoperability research, making it a 3 rather than a 5. Problem framing earns a 3 because the end user (AFGSC) and domain (air refueling training) are identified, but success criteria are loosely defined as 'measurable performance on utility' without concrete accuracy, latency, or adaptation-quality benchmarks.

Source

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