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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. 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
  2. Visual Augmentation Systems (VAS) Range Finder

    SBC: ATTOLLO ENGINEERING, LLC            Topic: SOCOM234003

    Augmentation Systems (VAS) Range Finder. It provides opportunities for day/night observation and range measurement in a small, easy-to-use device. We tradeoff features and SWAP-C to determine optimal combinations and document them in a feasibility study. Novel methods of presenting ranges are further. investigated and discussed.

    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. Hokkien Low Density Language Capability

    SBC: TOYON RESEARCH CORPORATION            Topic: SOCOM232002

    Toyon proposes to establish the feasibility of a novel approach to performing S2ST between a target language, such as English, and the low density spoken only language Hokkien. While we will focus of Hokkien during the research and development efforts of Phase I, our system can be tailored to any low density spoken language. Our approach leverages our recently developed Android Team Awareness Kit ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  5. 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
  6. 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
  7. Analyzing Narrative Evolution Across Social Networks

    SBC: APTIMA INC            Topic: SOCOM234001

    The modern information environment (IE) is growing more complex and dynamic. Information technology advances enable adversaries to access and influence audiences globally with increasingly sophisticated tools and at an unprecedented scale. To understand the threat landscape and to respond effectively, there is a need to automatically detect, track, and differentiate the evolution of information na ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  8. 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
  9. Topological Anomaly Detection

    SBC: CHARLES RIVER ANALYTICS, INC.            Topic: SOCOM224007

    Charles River Analytics and PatchPlus Consulting are pleased to propose Cerulean FNX, a modular software platform that extends Charles River’s Cerulean transaction analysis framework to the financial intelligence domain. Cerulean FNX is centered around a modular and pluggable network analytics engine containing state/of/the/art financial graph and time series analytics, a modular coordinated vis ...

    SBIR Phase I 2023 Department of DefenseSpecial Operations Command
  10. Detect and Identify Automated Labeler for Radar (DIALR)

    SBC: PRIME SOLUTIONS GROUP, INCORPORATED            Topic: OSD221002

    Detect and Identify Automated Labeler for Radar (DIALR)  Prime Solutions Group, Inc. (PSG) proposes Detect and Identify Automated Labeler for Radar (DIALR) for Research and Development (R&D) and demonstration of an algorithm framework for automated labeling of target classes in radar imagery. This provides a baseline for automatically labeling multiple target classes in Synthetic Aperture Radar ...

    SBIR Phase I 2022 Department of DefenseNational Geospatial-Intelligence Agency
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