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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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Enhanced Canine Performance, Protection and Survivability
SBC: Virtech Bio, Inc. Topic: SOCOM172002The goal of this Proposal is treatment of hemorrhage in SOCOM canines using a novel hemoglobin resuscitation fluid with oxygen carrying and plasma expansion properties (VIR-VET, a product of VirTech Bio). VIR-VET is designed to provide immediate hemodynamic stability and oxygenation to injured canines with blood loss. The product has advantages over traditional military fluid therapies: 1) As cell ...
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
Enhanced Canine Performance, Protection and Survivability
SBC: REJUVENATE BIO INC Topic: SOCOM172002Multi-Purpose Canines (MPCs) are an integral aspect of the US military. The continued expansion and use of these indispensable force multipliers in an intense, ever-changing and complex battlefield requires enhancing their innate capabilities in a timely manner. Additionally, canines have a relatively short life span, and considering the substantial training period that MPCs must undergo, their ef ...
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
Group 2 (<55lbs) Unmanned Aerial System for Special Operations Forces Tactical-Level Intelligence, Surveillance, and Reconnaissance Operations
SBC: THORPE SEEOP CORP Topic: SOCOM172005A technical approach is proposed to survey the industry for state of the art capabilities in terms of the SOCOM mission requirements described in the solicitation for the Group 2 Tactical ISR UAS. The results of the survey will select a configuration of potential candidate UAS that would meet the threshold and ultimately objective goals stated.
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
Handheld Hidden Chamber Detection
SBC: TIALINX, INC. Topic: SOCOM173004SOCOM requires rapid implementation and delivery of a handheld, automated hidden chamber sensor system to detect, locate, and discriminate hidden compartments. TiaLinxs Eagle-NC is a wall imager that operates as an ultra-wideband (UWB) radio frequency (RF) sensor integrated with advanced computer vision algorithms, state-of-the-art computer processor technologies, and has a fully integrated displa ...
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
Handheld Hidden Chamber Detection
SBC: VAWD APPLIED SCIENCE & TECHNOLOGY CORP Topic: SOCOM173004VAWD has extensive experience developing technologies and products for Sense Through The Wall (STTW) and RF Penetration through materials. Based on our experience we believe that the RF spectrum is a natural fit to solve this problem. Therefore we have constrained our trade space for an optimized microwave technology solution.VAWD proposes techniques that will use Multi-Frequency discrimination in ...
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
SUAS Killer, Identifier, and Tracker
SBC: Physical Optics Corporation Topic: SOCOM173005To address USSOCOMs need for a system to detect, locate, track, and either disable and/or destroy a small unmanned aerial system (SUAS) from a distance, Physical Optics Corporation (POC) proposes to develop the new SUAS Killer, Identifier, and Tracker (SKEET) system. The SKEET system is based on a new design that combines state-of-the-art airspace monitoring technology utilizing compact scanning r ...
SBIR Phase I 2018 Department of DefenseSpecial Operations Command -
Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia
SBC: HVMN Inc. Topic: SOCOM17C001In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Human Performance Optimization
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
System for Nighttime and Low-Light Face Recognition
SBC: Systems & Technology Research LLC Topic: SOCOM18A001Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency