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Award Data

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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.

  1. Low Cost W-Band Imaging Array

    SBC: MILLIMETER WAVE SYSTEMS LLC            Topic: CBD22BT001

    Low-cost systems operating at video rates within W-band have remained elusive – especially for stand-off and remote applications. Real time video rate imaging requires parallel detection modalities that traditionally led to high costs and calibration challenges. Substantial advances in low-cost packaging and chip-level integration driven by commercial millimeter-wave applications can now be appl ...

    STTR Phase I 2023 Department of DefenseOffice for Chemical and Biological Defense
  2. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: KRTKL INC.            Topic: SOCOM23B001

    krtkl (“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
  3. Multi-Dimensional Event Sourcing & Correlation- Publicly Available Information (PAI) (MDESC-P)

    SBC: PROGRAMS MANAGEMENT ANALYTICS & TECHNOLOGIES INC            Topic: SOCOM22DST01

    Multi-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
  4. Population Behavioral Analysis at Scale, AOR Modeling

    SBC: DEEP LABS INC            Topic: SOCOM22DST01

    Deep 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
  5. sUAS Munition Teaming for Advanced Precision Strike

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: SOCOM21C001

    Precision-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
  6. sUAS Munition Teaming for Advanced Precision Strike

    SBC: OPTO-KNOWLEDGE SYSTEMS INC            Topic: SOCOM21C001

    The 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
  7. Spray-based visual indicator of opioids for the rapid and effective decontamination of large areas

    SBC: TRITON SYSTEMS, INC.            Topic: CBD20AT001

    Triton Systems, Inc. will collaborate with The University of Massachusetts Lowell to develop a spray-based technology for the rapid, visual identification of opioids, turning contaminated areas from nondescript white powders to a brightly colored spots for easy recognition with the naked eye. The technology leverages molecular recognition units that bind strongly and specifically to a variety of o ...

    STTR Phase I 2021 Department of DefenseOffice for Chemical and Biological Defense
  8. Eye-readable Solution-based Dye Displacement Probe for Large-area Detection of Opioids

    SBC: INTELLIGENT OPTICAL SYSTEMS, INC.            Topic: CBD20AT001

    Intelligent Optical Systems, Inc., in collaboration with Bowling Green State University, proposes to develop a field-rugged, eye-readable indicating spray solution that can immediately detect synthetic opioids over a large area of contamination (i.e., military vehicles, individual protective equipment, clandestine labs, etc.). The proposed chemosensor in a spray solution format will detect multipl ...

    STTR Phase I 2021 Department of DefenseOffice for Chemical and Biological Defense
  9. Opioid Indicator Spray for Complex Surfaces

    SBC: Clear Scientific, LLC            Topic: CBD20AT001

    Opioids, especially synthetic opioids, are a constant threat to the safety of civilian first responders; there are now serious concerns about their use in modern chemical warfare. Fentanyl and its many analogues (carfentanil, remifentanil, lofentanil, mefentanil, sufentanil, etc.) are extremely hazardous—if ingested or inhaled, many synthetic opioids cause lethal intoxication with only a few gra ...

    STTR Phase I 2021 Department of DefenseOffice for Chemical and Biological Defense
  10. Algorithm Performance Evaluation with Low Sample Size

    SBC: SIGNATURE RESEARCH, INC.            Topic: NGA20C001

    The 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
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