PRIME SOLUTIONS GROUP, INCORPORATED — Department of Defense SBIR Phase II: OSD221-002
PRIME SOLUTIONS GROUP, INCORPORATED — SBIR Phase II award from Department of Defense.
Phase II SBIR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- Obligated amount $999,991 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
- Topic code OSD221-002 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $999,991
- Agency
- Department of Defense · National Geospatial-Intelligence Agency
- Program / Phase
- SBIR · Phase II
- Topic
- OSD221-002
- Solicitation
- 22.1
- NAICS
- —
- Place of performance
- AZ
- Period
- 2023-09-19 → 2025-09-04
Description
The 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 models creating even more demand of skilled analyst time. The cost of labeling by professional analysts is exacerbated further for Synthetic Aperture Radar (SAR) imagery because it is non-literal compared to electro-optical modalities, requiring more interrogation time. Prime Solutions Group, Inc. (PSG) proposes the Detect and Identify Automated Labeler for Radar (DIALR) SBIR Phase II program to develop and demonstrate a prototype algorithm that automatically detects, classifies, and labels targets in SAR imagery, including complex target collection scenarios. PSG’s innovative approach performs hierarchical classification within a taxonomy schema that aligns with NGA-Research’s Research Development Environment (RDE) taxonomy structure for seamless interaction between labeler and NGA-Research's pipeline management system. This combination of AI innovation and systems design will radically reduce data curation timelines and costs for the modeling mission of rapidly delivering derived information to decision makers.