Federal leaders are optimistic about using generative AI (GenAI) to transform the efficiency and effectiveness of mission operations. Yet many agencies still face barriers to advancing the technology from initial concept to real-world application. A new Booz Allen report, Building Enterprise Generative AI Applications, provides decision makers with the technical blueprint they need to engineer and deploy GenAI applications that meet government requirements for security, scalability, and overall performance.
Drawing from proven implementations, the Building Enterprise Generative AI Applications report details an architecture framework and set of practices that position your GenAI systems to powerfully enable the mission while being reliable, secure, and compliant with federal standards. Read our report for deep insights into:
- The advantages of harnessing a comprehensive GenAI tech stack
- The best model options, from on-premises and cloud to hosted application programming interfaces
- How to select large language models (LLM) based on task complexity and cost
- Special data pipeline requirements for domain-specific use cases
- The imperative to balance human oversight with autonomous agents
- Robust LLMOps practices for monitoring and improvement
- The strong governance, risk, and compliance frameworks needed for responsible AI use
