SBIR/STTR Research Award

DataForge: Multi-Domain Synthetic Data Generation

Award identifier 599718a3372ad1be41eaf8ca8182bd5671118eb32ed87c5d54d0656c89fc4574Awarding agency Department of Defense · Army

Award amount

$1,001,782

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
INTELLIGENT PAYLOAD SOLUTIONS, INC.
Proposal award date
2025-07-10
Contract end date
2026-07-14
UEI
WW3MMJ2QUNK5
Solicitation number
24.4
Topic code
A244-P037

Research abstract

The DataForge platform, developed by Intelligent Payload Solutions (IPS), is a cutting-edge synthetic data generation tool designed to address the increasing demand for high-quality, diverse datasets to train AI/ML models for defense applications. Current challenges in obtaining sufficient real-world data in critical domains such as missile defense, battlefield intelligence, and space operations limit the accuracy and performance of AI models. Traditional data collection methods, such as web scraping or purchasing, are slow and insufficient for the wide range of operational parameters the Army requires. DataForge leverages Generative Adversarial Networks (GANs) to produce large-scale, realistic synthetic datasets in visual, textual, geospatial, and sensor formats. These datasets are specifically tailored to simulate complex, real-world environments and scenarios, such as detecting anomalies in space operations and missile defense. By integrating this synthetic data into AI/ML model training, the Army can significantly enhance the performance of its systems, enabling faster, more accurate decision-making on the battlefield. The system architecture includes iterative GAN development and refinement, which ensures that the generated synthetic data closely mirrors the patterns found in real-world data. The platform will also support scenario-based simulations, creating controlled environments where AI/ML models can be tested and validated under various battlefield conditions. This approach ensures that the models are resilient and capable of detecting rare or critical events in operational scenarios. Through the development of DataForge, IPS aims to revolutionize how AI models are trained, offering a scalable and adaptable solution that can be applied across multiple Army-specific domains. The platform will integrate seamlessly with existing Army AI systems and enhance their ability to predict adversarial actions, track objects, and optimize defense strategies in complex, high-stakes environments. DataForge represents a critical step forward in enabling the Army to leverage advanced AI capabilities, ensuring the accuracy and reliability of machine learning models in diverse and contested environments.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

6 SBIR/STTR records share this UEI (2009–2025). Reported award amounts total $3,564,649. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Homeland Security

Agency intelligence

Department of Defense

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