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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. TheSieve

    SBC: CYBER POINT INTERNATIONAL LLC            Topic: None

    CyberPoint International presents the design of a cross platform product for the autonomous execution of live forensic investigations of Personal Computers, Laptops and Servers leveraging the NIST NSRL corpus and a combination of at least 3 forms of machine learning/artificial intelligent algorithms for the processing of preliminary digital evidence titled TheSieve. We build upon work from our pha ...

    SBIR Phase II 2019 Department of CommerceNational Institute of Standards and Technology
  2. Developing Commercial Quantum Resistance Standard Based on Epitaxial Graphene

    SBC: GRAPHENE WAVES, LLC            Topic: None

    Graphene Waves proposes to develop a quantum Hall resistance (QHR) standard based on graphene that can be deployed for general electrical calibration in industries. Current QHR standard is based on GaAs/AlGaAs heterostructure and requires expensive liquid helium to operate. The continuous increase in price and unstable supply chain of liquid helium limit the QHR standard to be only affordable by t ...

    SBIR Phase I 2019 Department of CommerceNational Institute of Standards and Technology
  3. Laser Particle Separation

    SBC: Opthos Instrument Company, LLC            Topic: None

    Parman Tech is dedicated to commercializing a NIST technology for sorting nano-particles. This technology uses the force of light to gently guide particles along different paths depending on the size of makeup of each particle.

    SBIR Phase I 2019 Department of CommerceNational Institute of Standards and Technology
  4. QGAN: Quantum Generative Adversarial Network to Secure Deep Learning

    SBC: Intelligent Automation, Inc.            Topic: SCO183001

    Despite deep neural networks have demonstrated tremendous success in various commercial and DoD applications, they are susceptible to adversarial attacks with detrimental outcomes to the underlying applications. The generative adversarial network (GAN) provides a good way of defending against adversarial learning attacks, but it is faced with a practical challenge, as classical computers are not a ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  5. Critical Program Information (CPI) Identification and Assessment Tool

    SBC: Technology Security Associates, Inc.            Topic: SCO183002

    TSA will assess the feasibility of developing or modifying an existing application-based process for creating: a) A functional architecture of a system to identify system missions, mission threads, and Critical Functions (mission model), and b) A physical architecture of a system (system model) in a manner consistent with both TSN Criticality Analysis and the Cybersecurity Risk Assessment Implemen ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  6. Scalable Low-Cost AESA Transmitter with Phase-Only Nulling

    SBC: PARRY LABS, LLC            Topic: SCO182002

    Parry Labs proposes the development and fabrication of a scalable, low-cost, transmit only wideband active electronically scanned array (AESA) operating in Ku band. Operating at Ku band maximizes aperture gain while also minimizing physical size and transmission loss due to rain and other atmospheric effects. The proposed system will be based on a scalable tile building block that can be used to c ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  7. Analog-Digital Hybrid ASIC Implementation of Miniaturized Neural Nets/Portmanteau Industries, LLC

    SBC: Portmanteau Industries, LLC            Topic: SCO182007

    The vision of truly autonomous, smart, and powerful edge devices requires the ability to perform intensive machine learning tasks with limited size, weight, and power budgets. We propose a highly efficient ASIC design that enables edge devices to achieve this vision.

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  8. A High-Throughput and Energy-Efficient Hardware Processor for Vision-based Object Detection Systems/Intelligent Automation, Inc.

    SBC: Intelligent Automation, Inc.            Topic: SCO182007

    We propose to design and implement a high-throughput and energy-efficient FPGA-based hardware processor (accelerator) for the deployment of Convolutional Neural Network (CNN) architectures at real-time embedded and resource-bound environments that have low size, weight, power and cost (SWaP-C) requirements. CNNs have been shown tremendous success in vision-based object detection tasks. Two differe ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  9. REMIX: REconfigurable Machine Intelligence eXtreme compute architecture/Intelligent Computing Machines, LLC

    SBC: INTELLIGENT COMPUTING MACHINES LLC            Topic: SCO182007

    We propose the analysis of a proposed architecture called ReMIX: Reconfigurable Machine Intelligence eXtreme compute architecture. This design is a chip multiprocessor with a non-von Neumann architecture and two layers of Network on Chip that enables low-power, high speed, parallel computations with very high throughput. Rather than have data traverse the memory hierarchy as is typical in von Neum ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  10. Deep Reinforcement Learning for Model Training with Simulated Imagery/Next Century Corporation

    SBC: Next Century Corporation            Topic: SCO182006

    Next Century Corporation proposes the development of the Computer Vision Synthetic Image Generation Harness for Training and Testing (CV SIGHTT), a prototype system that learns to train a generation-based image recognition system for low-shot detection in the remote sensing domain. CV SIGHTT will use Deep Evolution Strategies to select the procedure for synthetic image generation, choosing the one ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
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