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Virtualitics GenAI Toolkit Designed to Address Defense-Related Mission Readiness Challenges

Virtualitics GenAI Toolkit Designed to Address Defense-Related Mission Readiness Challenges - top government contractors - best government contracting event

Virtualitics has enhanced its artificial intelligence platform with the addition of its Generative AI Toolkit to improve decision-making across Department of Defense environments.

The toolkit is designed for deploying mission-specific AI agents that could enable faster, more informed decisions in defense sustainment, logistics and readiness workflows, Virtualitics said Thursday.

A foundational addition to the Virtualitics AI Platform, the GenAI Toolkit features tailored capabilities, including retrieval-augmented generation, which connects secure, trusted data sources to GenAI models for grounded responses; containerized large language models that are deployable on any approved system to keep sensitive data protected and models mission-specific; developer-ready interfaces that enable easy integration of GenAI capabilities into AI applications running on the Virtualitics AI Platform; and Readiness Sigma, a new domain-focused summarization capability.

The toolkit is not just generic LLMs for defense applications, said Rob Bocek, chief revenue officer at Virtualitics. They are engineered “from the front lines back, meeting operators where they are and helping them move faster with confidence.”

AI Agents for Mission Readiness

According to the company, unlike generic AI platforms designed for building AI agents from scratch, Virtualitics develops agents that can address readiness challenges, such as part shortages, sustainment planning and resource allocation, with each agent crafted to reduce decision burden, surface critical information from data silos and provide explainable outputs that align with human workflows.

The first AI agents for mission readiness built through the GenAI Toolkit will be ready this summer for use cases in predictive maintenance and materiel forecasting within existing integrated readiness optimization applications.

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Written by Kristen Smith

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