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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 Imaging In The mm Wave Region Using Plasma Waves in High Mobility Transistor

    SBC: BRIMROSE TECHNOLOGY CORP            Topic: CBD22BT001

    In this work, we propose to develop low-cost, high sensitivity high electron mobility transistor-based W-band millimeter wave focal plane array/camera based on mature ternary III-V epitaxial materials of InAlAs on top of InP substrate. The plasma-wave detector uses well established mature technology of high electron mobility transistors which allows future integration and reduces cost. The detecto ...

    STTR Phase I 2023 Department of DefenseOffice for Chemical and Biological Defense
  2. High Energy Density Batteries

    SBC: WASATCH IONICS LLC            Topic: SOCOM232003

    Soldiers conducting missions on foot in remote locations must carry multiple battery powered electronic devices, such as multiband radio sets, night vision goggles and scopes, GPS tracking, thermal imagers, target designators, etc. These devices allow soldiers to target, move, and communicate in the modern battlefield. Depending upon the type of mission and its duration, soldiers might not have th ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  3. Hokkien Low Density Language Capability

    SBC: FEMTOSENSE, INC.            Topic: SOCOM232002

    Femtosense is an innovative tech startup leading the charge to deploy sparse AI using novel techniques that are far more affordable and easier to implement than traditional AI computational technologies. Femtosense’s invention – the Sparse Processing Unit (SPU-001) is a TRL level 7 processing chip poised to disrupt the $50B AI hardware market. It offers best-in-class SWaP-C (Size, Weight, Powe ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  4. 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
  5. AI/ML Aided Aviation Sensors for Cognitive and Decision Optimization

    SBC: PARRY LABS, LLC            Topic: SOCOM23B001

    Existing airborne defense systems integrate a wide variety of sensors necessary to provide operators with situational awareness across the visual, thermal, signals, and electromagnetic spectrums. To date, individual sensor systems have been largely stove-piped, as have Artificial Intelligence/Machine Learning (AI/ML) and advanced, Size, Weight, and Power (SWaP)-optimized data processing systems. T ...

    STTR Phase I 2023 Department of DefenseSpecial Operations Command
  6. Visual Augmentation Systems (VAS) Range Finder

    SBC: Maztech Industries LLC            Topic: SOCOM234003

    IERUS is developing a novel phased array ground terminal aperture architecture for the DoD's next generation of satellite constellations. With the proliferation of high-bandwidth satellites across LEO, MEO, and GEO, there is a need for SWaP-C optimized user terminal apertures. The IERUS solution implements scalable and mission-set reconfigurable technologies to enable rapid transition into operati ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  7. An Artificial Intelligence (AI) – Based 3 Dimension (3D) Building Model Generation Capability for Chemical Biological Radiological and Nuclear (CBRN) Situational Awareness (SA) and Hazard Modeling

    SBC: AERIS LLC            Topic: CBD222005

    If successful, we will demonstrate the feasibility of the two technology elements that we believe are necessary to automate the development of photo-realistic 3D models of buildings that are physically consistent with the 3D model inputs for chemical and biological (CB) hazard estimation models. This will enable the development of a full capability that combines these elements into a fully automat ...

    SBIR Phase I 2023 Department of DefenseOffice for Chemical and Biological Defense
  8. Non-PFAS Omniphobic Liquid Repellent Coatings

    SBC: TDA RESEARCH, INC.            Topic: CBD222002

    Protective textiles are used in a wide range of military and civilian applications, including protective gear worn by U.S. military personnel in a toxic environment (e.g., during a chemical, biological, radiological, or nuclear strike). These garments must shield the wearer against a variety of liquids, including toxic industrial chemicals, pharmaceuticals, fuels, and chemical warfare agents. Thus ...

    SBIR Phase I 2023 Department of DefenseOffice for Chemical and Biological Defense
  9. Portable Working Dog CBRN Shelter

    SBC: TDA RESEARCH, INC.            Topic: CBD222003

    Military working dogs (MWDs) have been an integral part of the U.S. military since the Revolutionary War. Since Sept 11, 2001, the demand for these animals has increased and the number of animals trained/year has more than doubled. MWDs are frequently deployed into military field environments that can be hazardous, and they are highly susceptible to toxic chemical exposure. Protecting military wor ...

    SBIR Phase I 2023 Department of DefenseOffice for Chemical and Biological Defense
  10. Topological Anomaly Detection

    SBC: ADVANCED ONION, Inc.            Topic: SOCOM224007

    We propose a study to assess the feasibility and efficacy of using graph/based analytics and Graph Neural Networks (GNN) to identify anomalous individual and organizational personas in financial transaction datasets. Currently, there is an urgent and expensive need to deny nefarious transnational state and non/state actors from accessing global financial systems, export/controlled technologies, cr ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
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