Jane Edwards 
Jay Meil, vice president of strategic mission innovation and chief data scientist at SAIC, said retrieval-augmented generation with reasoning, or RAG-R, could be used as a method to turn large language models, or LLMs, into operational decision aids that could meet the demands of intelligence and national security environments.
Meil will be one of the featured speakers at the Potomac Officers Club’s 2026 Artificial Intelligence Summit on March 19. Join him and other technology experts for an engaging look at how AI is transforming industries and missions. Register now!
How Does RAG-R Support National Security Missions?
In an earlier post, Meil explored why LLMs fall short for military and intelligence missions, while in his latest post, the SAIC executive discussed why RAG-R works in intelligence and national security settings.
According to Meil, RAG-R could support warfighting and intelligence operations because it can be deployed in secure and classified environments, adapt to changing inputs and support governance and access-control policies.
He also described RAG-R as a mission-centric artificial intelligence strategy designed to enhance human decision-making.
“The RAG framework offers a clear methodology to bring the AI to the mission, rather than forcing the mission to conform to the AI,” Meil wrote. “It respects the information environment (classified, fragmented, fast moving) and gives operators the ability to interrogate, verify and adjust as necessary. It empowers decision-makers to use AI as a decision accelerator—giving minutes back to mission.”
What Is RAG-R?
In his earlier post, Meil said RAG-R combines the reasoning power of LLMs “with real-time access to authoritative, mission-specific data.”
Instead of relying on an LLM’s training data, Meil noted in his latest post that RAG-R allows the retrieval of relevant, authoritative mission data from curated document stores and feeds it into the model as context, allowing generative models to focus on reasoning and transforming them into operational decision aids suitable for national security environments by addressing their core limitations.
