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Award Data
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.
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STRATFI- BASECAMP SEQUENTIAL PHASE II
SBC: SIMBA CHAIN INC Topic: AF192001The STRATFI Earth 616 project will create a proof of concept secure Distributed Ledger Technology (DLT) based environment to provide near real-time visibility and traceability, along with associated securing of digital assets, for parts and data from an i
SBIR Phase II 2023 Department of DefenseAir Force -
Production of Pure Magnesium with Green technology from ore Materials-Dolomite and Magnesite
SBC: CROWN MAGNESIUM INC Topic: DLA232003Magnesium metal, sometimes referred to as the “Green Metal” is important for defense and industrial use, as it is the lightest of all the structural and engineering metals. Magnesium also has superior mechanical properties such as high dampening capacity, heat dissipation, and shock absorbing capacity. Magnesium is 100% recyclable. Due to these factors, magnesium metal is in high demand in the ...
SBIR Phase I 2023 Department of DefenseDefense Logistics Agency -
CYRIN-OT: Advanced Cyber Range for Operational Technology Digital Twins
SBC: ATC-NY INC Topic: DLA232004Industrial control system (ICS) operational technology (OT) systems enable increased process efficiency and cost savings. At the same time, they allow for increasingly complex cyber-attacks with devastating physical impacts. The ATC-NY team will design and build CYRIN-OT, a system for creating virtual “digital twins” of OT networks and performing security assessments on them. Any diverge ...
SBIR Phase I 2023 Department of DefenseDefense Logistics Agency -
VECSEL Based NV Diamond Magnetometry for Brain Machine Interfacing
SBC: CThru Lasers Inc. Topic: AF224D028Recent interest in high sensitivity magnetic sensing has spurred the development of several technologies, but none are ideal for Magnetoencephalography (MEG) imaging systems. The development of engineered diamonds with defects such as NV centers has been
SBIR Phase II 2023 Department of DefenseAir Force -
ACUMEN (Automated Consolidation of USAF Milestone Essential Notes) using Transformer ML Models
SBC: HEBBIA, INC. Topic: AF231D021Hebbia, Inc. (“Hebbia” or “Hebbia AI”) proposes to develop an innovative technology, ACUMEN (Automated Consolidation of USAF Milestone Essential Notes), to address the significant challenge facing the Air Force in managing acquisition milestone documentat
SBIR Phase II 2023 Department of DefenseAir Force -
Power Management for Energy Resiliency
SBC: PC KRAUSE & ASSOCIATES INC Topic: A224015Redacted.
SBIR Phase II 2023 Department of DefenseArmy -
IRIS: InfraRed Imager optimized for low SWAP
SBC: ALPHACORE INC Topic: A234013Redacted
SBIR Phase I 2023 Department of DefenseArmy -
Health Analysis from Vibrational Optical Characterization: HAVOC-Wear
SBC: Organic Robotics Corporation Topic: A224025Redacted.
SBIR Phase II 2023 Department of DefenseArmy -
DIALR Phase II
SBC: PRIME SOLUTIONS GROUP, INCORPORATED Topic: OSD221002The pace of remotely sensed data collection is increasing exponentially while the skilled workforce that is available to analyze and interpret the data is not. Artificial Intelligence (AI) offers a technology pathway to automation which promises to rapidly reduce the gap between data and information products and services. However, AI techniques require massive quantities of labeled data to train m ...
SBIR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency -
Multi-Task Scale-aware Continuous and Localizable Embeddings
SBC: KITWARE INC Topic: OSD22A001In Phase I, our team of Kitware and UC-Berkeley developed Scale-MAE by adding ground sample distance (GSD) to positional encodings, and produced a multiscale representation that achieves state-of-the art results across image classification, semantic segmentation, and object detection tasks. In Phase II, we will create a remote sensing pretraining toolkit to enable fast and easy experimentation wit ...
STTR Phase II 2023 Department of DefenseNational Geospatial-Intelligence Agency