REQUEST FOR INFORMATION (RFI) FOR GEOINT AI/ML ALGORITHM ORCHESTRATION FRAMEWORK

The Air Force Life Cycle Management Center (AFLCMC) Command and Control Intelligence, Surveillance and Reconnaissance (C2ISR) Division requires site support functions and logistics sustainment necessary to maintain capabilities for Global Network Systems. Through this requirement, the Government is seeking individuals with strong background and experience with algorithm management. These individuals must be able to perform higher integration and orchestration functions in the management and oversight of the architecture, its systems and programs. They must also possess an exceptional understanding of the fundamental principles of algorithm invocation and workflows for processing against geospatial imagery and integrating algorithm marketplace systems with existing complex geospatial processing capabilities.

THIS IS A REQUEST FOR INFORMATION (RFI) ONLY. This RFI is issued solely for information and planning purposes - it does not constitute a Request for Proposal (RFP) or a promise to issue an RFP in the future. This RFI does not commit the Government to contract for any service whatsoever. Further, the Air Force is not at this time seeking proposals and will not accept unsolicited proposals. Responders are advised that the U.S. Government will not pay for any information or administrative costs incurred in response to this RFI; all costs associated with responding to this RFI will be solely at the interested party's expense. Not responding to this RFI does not preclude participation in any future RFP, if any is issued.

Interested parties are requested to respond to this RFI by providing a company capability statement pertaining to the below areas of expertise. ONLY prime contractors shall complete a capability statement; however, prime contractors are able to include information provided by their subcontractors in their response. Capability statements shall not exceed 20 pages in length and must address the following:

a. GEOINT AI/ML Algorithm Orchestration Framework

Please describe your experience with modular design and open architecture approaches for integrating, testing, and hosting advanced algorithms and cataloging data in support of GEOINT exploitation. Detail experience handling the ingest of GEOINT products (imagery, geoJSONs, etc.) or data from external sources and performing automatic tasking, workflow management, or algorithm retraining/implementation accordingly. Include information on your experience with machine learning algorithm orchestration or algorithm repository implementations and other similar system-of-systems-based approaches.

b. GEOINT AI/ML Exploitation Applications

Highlight specific experience and discuss current/past projects involving any or all of the following:

- Exploitation of electro-optical (EO) and synthetic aperture radar (SAR) imagery

- Automatic target recognition (ATR) in EO/SAR imagery via AI/ML algorithms

- Point clouds and or 3D/4D generating volumes from EO/SAR imagery

- Synthetic target/object (CAD model) insertion into EO/SAR imagery

c. GEOINT AI/ML Algorithm Storefront & Repository Integration

Discuss your familiarity and any current or past projects hosting/supporting GEOINT or geospatial products, applications, or exploitation capabilities in a cloud-based environment. Highlight relevant experience with Air Force/DoD security accreditation of such environments and or the products that go in them. Provide information on your aptitude with Amazon Web Services, DAF Cloudworks, or other similar cloud-based services.

d. Test Support Capacity Detail your test support capabilities, including technical support for testing and integration of software applications into both on premise hardware and cloud-based environments. Include estimates on your ability to travel and support monthly Agile software release cycles at 3 different CONUS locations.

e. Digital Interface Capabilities Describe your experience and capabilities with digital interfaces, specifically citing standards such as MIL-STD-1760 or Built-In-Test (BIT) functionalities.

f. Modular Design Attributes and Open Architecture Detail any modular design approaches or open architecture protocols used within your solutions. Explain the benefits and flexibility these design attributes bring to the end-users.

g. Teaming Arrangements or Integration Partners List any teaming arrangements or integration partners that are part of your project implementations. Provide details on joint ventures or partnerships that enhance your project's success.

h. Production Capacity and Scale-Up Timeline Estimates Provide estimates of your production capacity to meet the scale required for large scale machine learning imagery processing implementations on government hardware. Include timeline estimates for scaling up production to meet demand.

i. Ability to Obtain/Maintain Clearances Describe your company's capability and processes to obtain new clearances (both for the company and for individual employees) as needed to support potential future work related to this Imagery Post Processing Capability. Include an estimated timeframe to obtain necessary clearances, if required.

Responses must be submitted electronically to Jared Duhaime, jared.duhaime.1@us.af.mil nolater than June 3, 2026, 5:00 PM EST. Proprietary information, if any, should be minimized and MUST BE CLEARLY MARKED. To aid the Government, please segregate proprietary information. Please be advised that all submissions become Government property and will not be returned. Verbal questions will NOT be accepted. Questions will be answered through email. The Government does not guarantee that questions received after June 3, 2026 will be answered.

cc: AFLCMC/ C3IWK (Jared I. Hines, jared.hines.1@us.af.mil; Sarah Mcdonough, sarah.mcdonough.2@us.af.mil; Marcel Bedard, marcel.bedard.ctr@us.af.mil; Timothy Lee, timothy.lee.15.ctr@us.af.mil)