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U.S. Department Of Justice·Alabama

Artificial Intelligence for Unmanned Aerial Systems

Closes 12/30/2025$500k – $5MRequest for Information
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Description

The Federal Bureau of Investigation (FBI) is seeking artificial intelligence (AI) and machine learning (ML) solutions for unmanned aerial systems (UAS). The AI/ML systems should be able to ingest real-time video feeds from manned or unmanned aerial platforms and provide object detection, license plate recognition, facial recognition, and perimeter detection. The systems should be able to run on-premises and optionally on Jetson Orin-equipped UAS platforms. The FBI is looking for companies that can provide these solutions and is requesting capability statements from interested parties. • The AI/ML systems should be able to detect objects such as vehicles, vessels, people, animals, and firearms. • The systems should be able to recognize license plates and faces. • The systems should be able to detect perimeters and provide direction of travel awareness. • The systems should be able to integrate with TAK and UAS Tool. • The systems should be EO/IR capable. • The systems should be able to run on-premises and optionally on Jetson Orin-equipped UAS platforms.

Attached files

Contact

Brian Ames(Contract Specialist)

[email protected]

Key dates

Opened
11/20/2025
Questions due
12/12/2025
Closes
12/30/2025

Last updated

Details

Type
Request for Information
Industry
Information Technology and Software Development
NAICS
541330
Solicitation №
RFI250003

Budget estimate

$500,000 – $5,000,000

The budget for this opportunity is difficult to estimate because the document does not provide a specific budget or funding amount. However, based on the complexity of the AI/ML solutions required, it is likely that the budget will be significant. The FBI is a large government agency with a substantial budget for technology and innovation. The budget could be in the range of $500,000 to $5 million, depending on the scope and duration of the project. The budget will likely be influenced by factors such as the number of UAS platforms, the complexity of the AI/ML solutions, and the duration of the project.

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