The “key facts” mode pulls structured fields directly from the official source posting (amount, deadline, eligibility tags). The AI mode adds a short plain-English narrative on top, generated from the same source. Always verify with the agency before applying.
AI-generated. Always verify with the official source.
Who can apply — at a glance
Eligible applicants:
see the Eligibility tab for the criteria from the official announcement.
Where:
Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming, District of Columbia.
Award:
Up to $1.5M.
Matching funds:
not required.
Deadline type: Fixed.
Compiled from the official listing's structured fields — always verify with the funder before applying.
Topic Funding Opportunities Back to Funding Opportunities Search AI-Enabled Computed Vision Air-to-Air Refueling Performance Assessment and Automated Pilot Debrief System Funding Agency DOW USAF Year: 2027 Topic Number: DAF27TZ01-DV001 Solicitation Number: 27.TZ Tagged as: STTR Phase II Solicitation Status: Closed NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For this reason, you should use the agency link listed below which will take you directly to the appropriate agency server where you can read the official version of this solicitation and download the appropriate forms and rules. View Official Solicitation Release Schedule Release Date October 7, 2026 Open Date October 28, 2026 Due Date(s) November 25, 2026 Close Date November 25, 2026 Description Air-to-air refueling (AAR) is a critical Department of the Air Force and Department of the Navy capability enabling global mobility, long-range strike, combat airpower projection, and sustained aviation operations. However, aerial refueling remains one of the most technically demanding and safety-critical aviation tasks performed by aircrews. Successful execution requires precise aircraft positioning, coordinated control inputs, accurate closure rate management, continuous situational awareness, and effective crew coordination between tanker and receiver aircraft.Current aerial refueling training and post-flight assessment processes rely heavily on instructor observation, pilot self-assessment, manual video review, and subjective evaluation of performance. These approaches provide limited ability to quantitatively assess the thousands of individual performance variables that influence successful refueling operations. Existing methods do not provide pilots with objective, moment-by-moment feedback on aircraft positioning, closure rates, control inputs, deviations from desired procedures, or trends in individual performance over time.This topic seeks to transition an artificial intelligence (AI)-enabled computed vision capability that (post-flight) automatically analyzes aerial refueling operations and provides objective, data-driven pilot performance feedback. The desired capability will mature existing advances in autonomous aerial refueling analytics and apply them toward safety improvement by transforming aerial refueling video and available aircraft performance data into actionable post-flight debrief products.The developed system shall provide an automated “hot wash” which analyzes aerial refueling events, identifies performance deviations, and generates intuitive visualizations that allow pilots and instructors to better understand execution quality and areas for improvement. The system shall reduce reliance on subjective recollection and manual review by providing objective measurements of aircraft performance throughout the refueling profile.The capability shall focus on analysis of tanker-mounted video data, such as KC-46 aerial refueling camera systems, while maintaining an architecture capable of expanding across additional tanker and receiver platforms. The vendor may pick (with Government concurrence) the first 3-5 receiver platforms to use in developing this system.
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Who can apply
Small Business Technology Transfer (STTR) eligibility: applicant must be a small business concern (<= 500 employees) partnered with a non-profit research institution (university or federally-funded R&D center). Small business performs at least 40% of the work; research institution performs at least 30%. | eligibility Apply Find Topics and Solicitations Frequently Asked Questions (FAQ) Lab to Market Hub Program Tutorials Community Stay connected with our innovation ecosystem Community Event Spotlight News and Events Newsletter Sign-up Federal and State Technology (FAST) Growth Accelerator Fund Competition (GAFC) Topic Funding Opportunities Back to Funding Opportunities Search AI-Enabled Computed Vision Air-to-Air Refueling Performance Assessment and Automated Pilot Debrief System Funding Agency DOW USAF Year: 2027 Topic Number: DAF27TZ01-DV001 Solicitation Number: 27.TZ Tagged as: STTR Phase II Solicitation Status: Closed NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For thi
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