SAM #APEXRFI032026

FAA RFI: Air Traffic Controller Academy Performance & Excellence System (APEX)

The Federal Aviation Administration (FAA) is seeking industry input for a scalable, data-driven Air Traffic Controller Academy Performance & Excellence System (APEX) to modernize training performance intelligence. - Government Buyer: - Federal Aviation Administration (FAA), Department of Transportation - Air Traffic Control Academy, Oklahoma City, OK - Contracting office: AAQ-30, FOB-10A, RM 400W, 800 Independence Ave SW, Washington, DC - Requested Solution: - Enterprise training performance intelligence system for Air Traffic Controller Academy - Must integrate disparate training data sources into a unified analytics environment - Provide near-real-time visibility into student performance across all training phases - Support predictive modeling, performance standardization, and strategic decision-making - Serve as foundational performance intelligence backbone for Academy operations and future enterprise expansion - Key Requirements: - Comprehensive data integration and objective-level mastery mapping - Analytics dashboards, error taxonomy and trend analytics - Predictive analytics, instructor performance analysis, and enterprise leadership reporting - Technical and security compliance, scalability, and implementation approach - Non-proprietary, interoperable, and scalable architecture - Optional demonstration materials and sample dashboards using representative data - No specific OEMs or vendors are named; responses should be suitable for public release - Place of Performance: - FAA Academy, Oklahoma City, OK - FAA contracting office, Washington, DC

Description

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

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