SchemaOne

The Department of the Air Force Materiel Command Lifecycle Management Center Joint Base San Antonio (AFLCMC) is seeking innovative commercial solutions to manage and validate high-volume data streams under the SchemaOne data standard through this Request for Information (RFI). Vendors must demonstrate capabilities across four primary pillars: Lifecycle Leadership & Governance with 24/7/365 on-call support for critical schema failures; Intelligent Data Mapping to ensure consistency across disparate data sources; High-Fidelity Transformation to convert raw data into SchemaOne-compliant formats with minimal latency; and Continuous Validation & 24/7 Health Monitoring to proactively detect irregularities. A critical evaluation differentiator is the integration of artificial intelligence and machine learning capabilities to enhance operational efficiency, provide AI-driven diagnostics for root-cause analysis of data failures, reduce time-to-field for new dataset transitions, and minimize false positive alerts. The solution must address configuration drift and data acquisition irregularities while maintaining SchemaOne standard integrity across time-series logs and cyber threat intelligence ingestion. The due date for this pre-solicitation notice is April 24, 2026.

This opportunity carries no set-aside designation and is classified under NAICS 541511 (Custom Computer Programming Services) and PSC DA01 (IT and Telecom - Business Application/Application Development Support Services). No incumbent contractors, award values, budget ranges, or specific quantity metrics are identified in the pre-solicitation notice. The RFI serves as an early market research tool to assess vendor capabilities and innovative approaches prior to formal solicitation, with no immediate contract award expected from responses to this notice. Interested vendors should review the detailed Problem Statement document provided to understand the full scope of the Air Force's requirements for managing consistency across diverse, voluminous datasets flowing continuously, where manual processes currently create bottlenecks and out-of-cycle data breaks result in potential data loss or corruption.