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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
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AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization
SBC: KRTKL INC. Topic: SOCOM23B001krtkl (“critical”) will conduct a Phase I Feasibility Study to identify the best approach for reducing aviator cognitive load by optimizing information delivery and decision-making based on a thorough analysis of existing platforms, sensors, data sources, and onboard compute resources. This information will be used to identify Artificial Intelligence and Machine Learning based algorithms for p ...
STTR Phase I 2023 Department of DefenseSpecial Operations Command -
SeaCraft/AeroNautical Data-collector (SCAND) for real-time target recognition
SBC: HYDRONALIX INC Topic: SOCOM22DST01Artificial intelligence-assisted detection and imaging technology can gather data on underwater, surface, and aerial threats to gain situational awareness over opposing forces, and aids in navigating dangerous marine and terrestrial environments. Successful and efficient use of intel is crucial for strategic information warfare, but many current technologies require active monitoring to identify t ...
STTR Phase II 2023 Department of DefenseSpecial Operations Command -
Population Behavioral Analysis at Scale, AOR Modeling
SBC: DEEP LABS INC Topic: SOCOM22DST01Deep Labs recognizes USSOCOM’s challenge to process multiple data and communications inputs for optimized decision making, and to support rapid on-the-move abilities to learn and communicate knowledge to enhance tactically relevant situational awareness in peer/near peer environments. Deep Labs has proven this capability across complex challenges in the world’s largest commercial enterprises a ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
Multi-Dimensional Event Sourcing & Correlation- Publicly Available Information (PAI) (MDESC-P)
SBC: PROGRAMS MANAGEMENT ANALYTICS & TECHNOLOGIES INC Topic: SOCOM22DST01Multi-Dimensional Event Sourcing & Correlation - Publicly Available Information (PAI) (MDESC-P) will support collection jointly across disparate PAI sources with coordinated cueing of more constrained intelligence, surveillance, target acquisition, and reconnaissance (ISTAR) sources. The primary objective for MDESC-P is to deliver a scalable and automated PAI collection management solution using a ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
SeaCraft / AeroNautical Data-collector (SCAND) for real-time target recognition
SBC: HYDRONALIX INC Topic: SOCOM22DST01Intelligent detection and imaging technology hold considerable value for Department of Defense to attain situational awareness and advantage over opposing forces, and for aid in navigating potentially dangerous marine and terrestrial environments. Technologies obtain intelligence on underwater threats and can gather intelligence on approaching surface threats. Current sensor technologies require a ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
sUAS Munition Teaming for Advanced Precision Strike
SBC: CHARLES RIVER ANALYTICS, INC. Topic: SOCOM21C001Precision-guided munitions have demonstrated dramatic effects with minimal collateral damage. New technology developed specifically to deny them accurate guidance information is now feasible, even for non-traditional adversaries. Further, digital communications are flooding the air with signals that interfere with communications many guidance methods rely on. Swarms of small, covert small Uncrewed ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
sUAS Munition Teaming for Advanced Precision Strike
SBC: OPTO-KNOWLEDGE SYSTEMS INC Topic: SOCOM21C001The US requires standoff precision strike capabilities in GPS-denied and high threat environments. This includes fire-and-forget lock-after-launch vision-based guidance for SOPGM. Due to emerging threats, a paradigm shift is occurring in the way we gather intelligence, maintain surveillance, and perform reconnaissance. ISR platforms are evolving, and artificial intelligence is at the forefront of ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
Bounding generalization risk for Deep Neural Networks
SBC: Euler Scientific Topic: NGA20A001Deep Convolutional Neural Networks (DCNNs) have become ubiquitous in the analysis of large datasets with geometric symmetries. These datasets are common in medicine, science, intelligence, autonomous driving and industry. While analysis based on DCNNs have proven powerful, uncertainty estimation for such analyses has required sophisticated empirical studies. This has negatively impacted the effect ...
STTR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency -
Human Performance Enhancement
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special Operations Forces (SOF) operators are among the most elite, and highly qualified individuals in the U.S. military. Extraordinary physical and mental demands are placed upon them, to include superior performance standards, high operational tempos, and the pressure to excel in extreme environments for extended periods of time. In the SOF community, serious injuries are the norm rather than t ...
STTR Phase II 2021 Department of DefenseSpecial Operations Command -
Algorithm Performance Evaluation with Low Sample Size
SBC: SIGNATURE RESEARCH, INC. Topic: NGA20C001The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...
STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency