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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. Additive Manufacturing Process Monitoring and Control Technologies

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA181002

    This project aims to make Laser Powder Bed Fusion (LPBF) additive manufacturing a practical tool for supply chain management for the Defense Logistics Agency.The key step is developing process standardization to make LBPF quality vendor independent. This project will seek to demonstrate the use of a promising high speed melt pool monitoring device as a practical means to establish such process sta ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  2. Additive Manufacturing Process Monitoring and Control Technologies

    SBC: Made In Space, Inc.            Topic: DLA181002

    Made In Space, Inc. (MIS) and Siemens PLM Software propose an integrated Automated Processing. Monitoring, Control and Remediation System (Aul) to provide a process monitoring and control capability. Made In Space, Inc. leads the effort based on integrating Made In Space, Inc., proven inspection sensors systems with a Digital Thread for Additive Manufacturing (DTAM) system, co-developed by Siemens ...

    SBIR Phase I 2018 Department of DefenseDefense Logistics Agency
  3. Advanced Simulated Patient Intelligent Response Engine (ASPIRE)

    SBC: VCOM3D INC            Topic: DHA191002

    The goal of medical simulation-based training such as high-fidelity manikin simulators, part task trainers, and screen-based virtual patients, is to approximate real-life treatment experiences without risk to live patients. While the use of sensors has ma

    SBIR Phase I 2019 Department of DefenseDefense Health Agency
  4. Anatomic 3D Synthetic Tissue Printer for Medical Training

    SBC: SERAPH ROBOTICS, INC.            Topic: DHP12003

    Military medical personnel are not prepared to provide trauma care to severely injured soldiers in wartime due to inadequate and unrealistic battlefield training opportunities during peacetime. Training has historically been done on human cadavers and live animals, but cadavers are in limited supply, and animal rights groups and physicians are increasing pressure to end the practice of using live ...

    SBIR Phase I 2013 Department of DefenseDefense Health Agency
  5. Asynchronous Multi-transmitter Multi-aperture Synthetic 3D Imaging System

    SBC: VOXTEL, INC.            Topic: NGA183001

    Traditional active 3D imaging systems, such as airborne and terrestrial lidar scanners, use a transmitter and receiver typically co-located on the same platform and connected in synchronous communications. However, recent advances in laser, detector, and airborne systems technology have opened the door to smaller, higher-performance and significantly lower-cost airborne lidar systems in which it i ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  6. Augmented Reality Surgical Visualization

    SBC: CFD RESEARCH CORPORATION            Topic: DHA191001

    Care for the wounded Warfighters in austere and remote settings makes medical knowledge, skills and efficiency of the military medical professional paramount. For wounds that extend deep into internal anatomy, proper visualization of internal anatomy can

    SBIR Phase I 2019 Department of DefenseDefense Health Agency
  7. A User-Centric Gamified Crowdsourcing System for Geospatial Analysts

    SBC: 361 INTERACTIVE LLC            Topic: NGA191007

    Creating comprehensive geospatial datasets requires that National Geospatial Agency (NGA) analysts spend large amounts of time searching for, delineating, and labeling non-moving features in overhead imagery. This tiresome and tedious task can negatively impact not only the analysts’ work satisfaction but also the resulting data quality. Fortunately, recent advances in gamification and crowdsour ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Automating Procedural Modeling of Buildings from Point Cloud Data

    SBC: DIGNITAS TECHNOLOGIES, LLC            Topic: NGA183002

    Newer techniques in data collection such as Lidar and photogrammetry can provide large quantities of accurate and up-to-date source data models in operational areas, but transforming this often massive amount of raw source data into a lightweight 3D representation that can be quickly consumed by defense customers using a web browser or mobile devices remains a challenging problem. While point clou ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  9. Boost- A System to Suppress False Alarms from Automated Target Recognizers

    SBC: SEED INNOVATIONS, LLC            Topic: NGA181003

    Seed Innovations and subcontractor BIT Systems, a division of CACI International, apply our experience in machine learning, data analytics andimage processing to accomplish the research for the SBIR topic: Suppression of false alarms in Automated Target Recognizers (ATR) that useMachine Learning. With the amount of available imagery data increasing and adversaries vehicles and tactics becoming mor ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Collaborative Recommender System for Spatio-Temporal Intelligence Documents

    SBC: NUMERICA CORPORATION            Topic: NGA191005

    US military and intelligence agencies have invested significant resources in data collection and effective search and analytics tools. However, due to increasing amounts of data, finding relevant information has become more difficult. Thus, there is an important need for recommender system technology that pushes relevant un-queried data to analysts through automation and machine learning technique ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
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