Army selects SAAZ for AI/ML Innovation Research Contract

Army selects SAAZ for AI/ML Innovation Research Contract

WASHINGTON – The U.S. Army has awarded nearly $19 million to 23 small businesses to develop their artificial intelligence and machine learning solutions that will lead to more informed Army decision-making, facilitate autonomous operations and increase the speed and scale of military action.

The awards are in response to seven contract opportunities released by the Army Applied Small Business Innovation Research Program for U.S.-based small businesses to propose technologies in the areas of electronic warfare, sensors, information systems, battlespace environments and human systems.

Fourteen of the 23 small-business awardees received Phase I contracts for up to $250,000 to focus on the scientific, technical and commercial merit and feasibility of their innovations. The program also awarded nine companies Direct to Phase II contracts of up to $1.7 million each for small businesses ready for the prototyping stage.

Natural language processing, one of the contract opportunities, is a powerful tool that improves situational awareness and understanding for the Soldier, according to Dr. Bridgette Latimer, Army PEO Intelligence Electronic Warfare and Sensors

and technical point of contact for one of the SBIR topics.

“We are looking for these companies to develop AI/ML prototypes that can be transitioned into intelligence systems and analytics products,” Latimer said. “These companies have a very good grasp of the problem domain and the Army’s mission needs, so forming partnerships with them now will enable the Army to improve and advance the current state-of-the-art technology.”

The Army looks forward to working with the following companies:

  • Alphacore, Inc. (Tempe, Ariz.) for ANDROMEDA: Asynchronous Neuromorphic Detector Read-Out with ML-Enabled Digital Architecture
  • Arete Associates (Northridge, Calif.) for Army Automated Burst Localization Engine (AABLE)
  • Barron Associates, Inc. (Charlottesville, Va.) for Graph-Based Collaborative Autonomy for Intelligent Agents
  • Cenith Innovations, LLC (Sacramento, Calif.) for Modern Approaches to Breaching Minefields
  • Charles River Analytics, Inc. (Cambridge, Mass.) for Statistical Text Analysis with Training Semantics (STATS)
  • CLOSTRA, Inc. (Miami, Calif.) for GNN-SWARM and DeepHOB
  • EpiSys Science, Inc. (Poway, Calif.) for Real-Time Processing and Multiple Signal Classification (RAP-MUSIC) of a Wide RF Spectrum
  • Expedition Technology, Inc. (Herndon, Va.) for Photon SIGINT/EW AI/ML Services (SEAMS)
  • HyPerComp, Inc. (Westlake Village, Calif.) for Synthetic RF Training Data Generation
  • InferLink Corporation (El Segundo, Calif.) for Targetable NLP
  • Intellisense Systems, Inc. (Torrance, Calif.) for Radiofrequency One-Shot Learning for Emission Recognition
  • Language Computer Corporation (Richardson, Texas) for Automatic Detection of Analyst-Relevant Nuggets (ADORN)
  • Nu-Trek (San Diego) for Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles
  • Outside Analytics, Inc. (Broomfield, Colo.) for Machine Learning (ML) for Breach Routing
  • R-DEX Systems, Inc. (Marietta, Ga.) for The Virtual RF (VRF) System for Improved RF Synthetic Data Generation
  • SAAZ Micro, Inc. (Thousand Oaks, Calif.) for Third Gen Improved FLIR (TGIF)
  • Scientific Systems Company, Inc. (Woburn, Mass.) for NO-AnGSST: Neuroevolutionary Optimization of Aggregation-GNNs for Scalable Swarm Tactics
  • SciX3, LLC (Alexandria, Va.) for Height of Burst Scoring through Machine Learning and Machine Learning for Breach Routing
  • Soar Technologies (Palos Hills, Ill.) for DeepGraph
  • Space Micro, Inc. (San Diego) for Artificial Intelligence/Machine Learning (AI/ML) for Radio Frequency (RF) Modulation Recognition
  • University Technical Services, Inc. (Greenbelt, Md.) for RF-Based Automated Training Data Generation Engine (RF-AIDE)

“These companies are excellent models for how we’re harnessing small business ingenuity to meet critical Army AI and ML needs,” said Dr. Matt Willis, director of Army Prize Competitions and the Army Applied SBIR Program within the Office of the Assistant Secretary for the Army for Acquisition, Logistics and Technology. “The awardees showed novel approaches for how their technologies intersect Army needs and their strategy to commercialize their products. We decided to move forward to get them the funding they need, as well as direct feedback from the Army subject matter experts, to advance their solutions and transition them into the hands of Soldiers.”

In addition to benefiting the Army, the Applied SBIR Program offers a valuable opportunity for small businesses to interact with Soldiers and technical and operational subject matter experts, who provide insight into technology needs and guide small businesses through the Army research and development ecosystem. Small businesses are teamed up with technical points of contact from Army program offices that serve as a resource for companies as they mature their technologies for insertion into programs of record.

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