Foundation Digital Twin Auto Feature Extraction (FDT AFE)
Dept of Defense · NATIONAL GEOSPATIAL-INTELLIGENCE AGENCY (NGA)
This notice is not accepting responses (deadline was Mar 30, 2026, 5:00 PM EDT).
Page kept for research and related open opportunities below. For current work in this category, use the related notices or browse hubs.
- Response deadline
- Mar 30, 2026, 5:00 PM EDT
- Posted
- Mar 5, 2026
- Solicitation
- RFI-HM0476-03052026
- Set-aside
- None listed
- PSC
- —
- Place of performance
- USA
- Contracting office
- NATL GEOSPATIAL-INTELLIGENCE AGENCY · ARNOLD · MO
- Source
- SAM.gov · updated Jul 5, 2026
Description
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 supply or service whatsoever. Further, NGA is not seeking proposals at this time 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. NGA has a mission-critical need for implementing the Automated Feature Extraction (AFE) to improve efficiency and effectiveness in mission data feature collection. This RFI seeks industry input on available out-of-the-box AFE capabilities and how they can be provided as a service to support NGA operations to automatically detect and extract geospatial features from various data input sources, including imagery and raster maps, to meet the objectives described within Attachment 1 - AFE Statement of Objectives (SOO), section 4.0. In accordance with Attachment 2 titled �FDT AFE RFI� Section 4.4, Responses are due no later than 5:00 pm ET on 30 March 2026. Responses shall be limited to and submitted via e-mail only as a message attachment to Dan Fadely at Daniel.R.Fadely@nga.mil and Dee Hill at Delores.M.Hill@nga.mil with the message subject line �RFI Response � Foundation Digital Twin Automated Feature Extraction . This RFI is only intended for the Government to identify sources that can provide the services needed to fulfill the Government�s SOO. The information provided in this RFI is subject to change and is not binding to the Government. The Government has not made a commitment to procure any of the RFI requirements discussed, and release of this RFI should not be construed as such a commitment or as authorization to incur cost for which reimbursement would be required or sought. All submissions become Government property and will not be returned.
What similar awards have paid
Real federal awards already on the books in a similar lane — so you can size the opportunity, not guess. This is public history, not a bid price, cost estimate, or prediction that you will win.
Typical award size
$552,704
Middle of the pack for similar past awards
Most similar awards fall between $149,922 and $1.98M
Who has won work like this
Public awardees in this lane — useful for competitor scan or teaming ideas, not a ranked list of “best” firms.
- 1CALIFORNIA INSTITUTE OF TECHNOLOGY502 awards$17.96B
- 2FLUOR MARINE PROPULSION, LLC1 award$13.40B
- 3SPACE EXPLORATION TECHNOLOGIES CORP.2 awards$3.06B
- 4LEIDOS BIOMEDICAL RESEARCH INC115 awards$2.89B
- 5AMENTUM TECHNOLOGY, INC.53 awards$1.81B
- 6THE JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY LLC74 awards$1.78B
- 7FERMI FORWARD DISCOVERY GROUP, LLC1 award$1.73B
- 8BLUE ORIGIN WASHINGTON, LLC1 award$1.69B
Drawn from official USAspending contract records in our index. Always confirm requirements on the SAM.gov notice before you bid.
Intelligence only — not legal advice or a guarantee of award. Always verify requirements on the official SAM.gov notice. Past award amounts are public history, not a suggested bid or prediction. Notice ID e739aa1d98e046d08ad5d6471e42729b.