IvySys Technologies Awarded the DoD’s Joint Artificial Intelligence Center’s (JAIC) Data Readiness for Artificial Intelligence (DRAID) Basic Ordering Agreement

Company Extends Synthetic Data Generation Capabilities to Enable DoD AI Model Development

IvySys Technologies, an innovative synthetic data solutions and services company, announced that it has been awarded a Basic Ordering Agreement (BOA) for the Joint Artificial Intelligence Center (JAIC) Data Readiness for Artificial Intelligence Development (DRAID) program. With a ceiling value of $241.6 million, the five-year BOA will allow DoD components to rapidly access IvySys synthetic data generation solutions and related AI data preparation services. On behalf of the JAIC, the U.S. Army Contracting Command has awarded the DRAID BOA to establish a decentralized vehicle that streamlines rapid procurement and agile delivery of AI data readiness capabilities for the DoD.

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“The high cost to curate and produce quality problem-specific training data serves as a significant obstacle to the widespread adoption of AI in the DoD.”

“The high cost to curate and produce quality problem-specific training data serves as a significant obstacle to the widespread adoption of AI in the DoD.” said Dr. James A. DeBardelaben, President and CEO of IvySys Technologies. “IvySys is excited to bring forward our proven AI-driven synthetic data generation and automated data preparation capabilities as we partner with the JAIC to confront this mission critical challenge.”

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The solutions and services addressed by the DRAID vehicle span the full set needed to prepare “AI ready” data, from data ingestion right up to before AI model training begins. This JAIC DRAID contract builds on IvySys Technologies’ extensive experience supporting the DoD and Intelligence Community. As part of a recent DoD innovation program, IvySys developed a novel, generative AI-based synthetic data generator that employs user-specified threat scenarios to produce multi-source synthetic data for AI model training and testing, while protecting data privacy.

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