Air Traffic Controller Academy Performance & Excellence System (APEX) APEXRFI032026
Summary
AI-generated · Mar 31, 2026FAA is seeking concept-level input for an Air Traffic Controller Academy Training Performance Intelligence System (APEX). The goal is a scalable, data-driven, near real-time analytics backbone that unifies disparate academy training data into an enterprise analytics environment, enabling predictive modeling, performance standardization, and strategic decision-making across all phases of Academy training. The system should be interoperable, extensible, and capable of supporting future enterprise expansion, rather than a standalone reporting tool or content delivery enhancement.
Respondents should submit concept papers with an implementation plan that covers: comprehensive data integration, objective-level mastery mapping, near real-time analytics dashboards, error taxonomy and trend analytics, predictive analytics, instructor performance analysis, enterprise leadership reporting, and the technical/security requirements, scalability, and future expansion approach. Optional demonstration materials may include sample dashboards. Responses must be suitable for public release, with no confidential information, and this is not a commitment to issue an RFP or pay for the information.
This Request for Information (RFI) includes a Statement of Objectives (SOO) which describes the Federal Aviation Administration s (FAA) goals and expectations for the implementation and operation of the ATC Training Performance Intelligence System. The FAA seeks concepts, approaches, and general capabilities only; please do not submit proprietary, trade secret, or confidential information. All responses should be written at a level that can be released publicly without restriction. The FAA seeks a scalable, data-driven system capable of providing near real-time visibility into student performance across all phases of Academy training. The FAA seeks a modern, adaptive solution that can serve as an enterprise training performance intelligence backbone. The FAA intends for this solution to function as an enterprise-level training performance intelligence infrastructure, forming a scalable data architecture that integrates disparate training data sources into a unified analytics environment. The system must serve as the foundational performance intelligence backbone for Academy training operations and future enterprise expansion. The FAA does not seek a standalone reporting overlay or content delivery enhancement tool; rather, the solution must establish an interoperable, extensible enterprise data framework capable of supporting predictive modeling, performance standardization, and strategic decision-making. The FAA requests that respondents provide concept papers identifying real-world solutions, along with an implementation plan that, at a minimum, addresses the following areas: Comprehensive Data Integration Objective-Level Mastery Mapping Near Real-Time Analytics Dashboards Error Taxonomy and Trend Analytics Predictive Analytics Instructor Performance Analysis Enterprise Leadership Reporting Technical and Security Requirements Scalability and Future Expansion Implementation Approach Nature of this RFI: (a) This is not a commitment to issue a further screening information request or request for proposals. (b) The FAA is not seeking or accepting unsolicited proposals. (c) The FAA will not pay for any information received or costs incurred in preparing any response to this RFI. (d) Any costs associated with any response to this RFI are solely at the interested vendor s expense. (e) The FAA does not seek and will not review proprietary, trade?secret, or confidential information in response to this RFI. Responses should be written so they can be made publicly available. Optional: Demonstration materials Sample dashboards using representative data
From Sources Sought posted on Mar 30, 2026Notice history
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Agency
Place of Performance
USA