Operationalizing Private AI for Federal Missions

As generative AI platforms like ChatGPT, Claude, Copilot, and Gemini become more prevalent, federal agencies are exploring how to harness AI capabilities while maintaining control over sensitive data, infrastructure, and mission-critical operations. Public cloud-based AI models offer scale, but they often fall short on security, transparency, and compliance — especially for defense, intelligence, and civilian agencies operating in classified, tactical, or disconnected environments.

This webinar will explore the strategic and technical pathways to deploying private, agentic-ready AI platforms tailored to federal use cases. From on-premise data centers to tactical edge deployments, we'll discuss how visibility into AI behavior, infrastructure validation, and performance assurance are essential to building trustworthy and resilient AI systems.

Join federal and industry experts as they share insights on building custom AI platforms that meet the unique demands of government missions — without relying on opaque, public LLMs.

We'll Discuss:

• Identify mission-specific challenges in deploying AI at the tactical edge, including disconnected operations, compute limitations, and environmental constraints.
• Evaluate validation and visibility strategies for ensuring performance, reliability, and trust in private AI platforms across federal environments.
• Assess infrastructure and compliance considerations for agencies deploying AI on-premise or in hybrid environments, including FedRAMP, CMMC, and zero trust architectures.
• Define key requirements for hosting agentic-ready AI systems, including observability, lifecycle assurance, and secure integration with existing federal IT ecosystems.