You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

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. Printable Dielectric for Flexible Hybrid Electronics

    SBC: ChemCubed, LLC            Topic: 2

    The goal for this Phase I research is to develop a stretchable dielectric ink that can be used for flexible applications. Printing electronics is a new and quickly growing alternative to traditionally manufactured electronics. Flexible hybrid electronics (FHE) is a novel approach to electronic circuit manufacturing that aims to combine the best of printed and conventional electronics. FHE devices ...

    SBIR Phase I 2023 Department of CommerceNational Institute of Standards and Technology
  2. Affordable Wastewater Disposal for Coastal Households Adapting to Sea Level Rise

    SBC: WAIHOME LLC            Topic: 92

    "Rising sea levels and king tide flooding in coastal areas across America are saturating onsite wastewater disposal systems (OSDS), resulting in the degradation of coastal ecosystems and 200,000+ illnesses annually. Many States are mandating system upgrades, with 88,000 upgrades required by 2050 in Hawaii alone. Unfortunately, existing upgrade options are unaffordable for 97% of Hawaiian homeowner ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  3. Carbon-Negative Oceanit Reef for Aquatic Life (CORAL) Surveying via Hyperspectral Imaging-Equipped Littoral Drones (SHIELD)

    SBC: OCEANIT LABORATORIES INC            Topic: 93

    Oceanit proposes the design, construction, and testing of a hyperspectral imaging equipped Unmanned Aerial System (UAS) for the detection of various coral species and the monitoring of coral health. This system will be the prototype for the sensor part of a robust, COTS-based UAS system to aid the NOAA National Coral Reef Monitoring Program. Different coral families and species will be identified ...

    SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration
  4. CodeSurgeon: Sound Full-Stack AI-driven Software Debloating

    SBC: TRAIL OF BITS INC            Topic: N23AT009

    We propose to develop and transition CodeSurgeon: an adaptable, AI-guided, full-stack debloating system. CodeSurgeon is innovative and unique in the field because it produces high-quality debloated programs with improved security posture that are safe, reliable, and sound. Following the lessons learned from a broad comparative evaluation of debloating tools conducted by the PI , CodeSurgeon will i ...

    STTR Phase I 2023 Department of DefenseNavy
  5. Realistic UUV Data Transformation Tool

    SBC: MAKAI OCEAN ENGINEERING INC            Topic: N23AT013

    Undersea target recognition from sensor systems onboard unmanned underwater vehicles (UUVs) play a critical role in the US Naval strategies and mission capabilities. Machine Learning provides a game-changing opportunity for improved Automated Target Recognition (ATR), but current attempts remain limited due to a lack of adequate training data. ML-based ATR algorithms are statistics-based systems; ...

    STTR Phase I 2023 Department of DefenseNavy
  6. Automatic Target Recognition (ATR) in Complex Underwater Environments

    SBC: BLACK RIVER SYSTEMS COMPANY, INC.            Topic: N231035

    Black River Systems Company, Inc. proposes a novel online machine learning (OML) solution for underwater ATR using acoustic, magnetic, and EO sensors. The proposed solution, called TRACE (Target Recognition Aided by Continuous Evolution), will utilize tailored feature extractors and a robust online Bayesian classifier to maximize ATR performance in challenging underwater environments. TRACE is des ...

    SBIR Phase I 2023 Department of DefenseNavy
  7. Incremental Online Learning for Target Recognition

    SBC: MAKAI OCEAN ENGINEERING INC            Topic: N231035

    Undersea target recognition from unmanned underwater vehicles (UUVs) plays a critical role in the US Naval strategies and mission capabilities. The current Automated Target Recognition (ATR) solutions remain limited to homogenous and similarly non-complex seabed environments. ATR in cluttered environments poses significant challenges, with automated solutions resulting in too many false alarms. Ma ...

    SBIR Phase I 2023 Department of DefenseNavy
  8. Eliminating ATR False Alarms in Complex Underwater Environments with Continuous Learning

    SBC: Neureon Incorporated            Topic: N231035

    AI technologies, such as deep neural networks (DNN), have entered a rapid ascent phase during which they will make significant contributions to the economy and society. It is critical that machine learning is exploited fully for national defense. The easiest deployment of DNNs for the Navy is evaluating growing data sources for intelligence and actionable information. One challenge with this appli ...

    SBIR Phase I 2023 Department of DefenseNavy
  9. Autonomous Multi-Perspective Hierarchical Centralized Fault Monitoring System

    SBC: SINGULARITY - INTELLIGENCE AMPLIFIED, LLC            Topic: N231055

    Singularity-Intelligence Amplified, LLC (Singularity-IA) proposes the development of a multi-perspective hierarchical Centralized Fault Monitoring System (CFMS).  We plan to pursue a Modular Open Systems Approach (MOSA) by dividing the CFMS functionality into three portions: data import, data storage, and visualization.  We plan to develop each of these functions as separate modules, allowing th ...

    SBIR Phase I 2023 Department of DefenseNavy
  10. Express Forensic Memory

    SBC: EXCELLERIX, LLC            Topic: N221071

    Excellerix proposes to build, test, and demonstrate a forensic memory solution, called EXFORM, exceeding the required threshold performance in delay and data throughput. By the end of Phase I Base, EXFORM was built and comprehensively tested with less than 1e-12 bit-error rate and data rates up to 200 Gbps. In Phase II we will build, demonstrate and deliver EXFORM as a rugged unit ready for Naval ...

    SBIR Phase II 2023 Department of DefenseNavy
US Flag An Official Website of the United States Government