Term explanation
AI guardrails are controls and constraints built into an AI system to limit what it can do, access, or produce. They define the boundaries of autonomous behavior: preventing an agent from accessing unauthorized data, generating off-brand content, or taking irreversible actions without approval. In enterprise environments, guardrails work alongside human-in-the-loop checkpoints to ensure that Agentic AI automation delivers efficiency without compromising security, brand integrity, or regulatory compliance.
LIZ AI is deployed with enterprise-grade guardrails: permissions, brand rules, and content policies that ensure every automated presentation action stays within the boundaries your organization defines.
Learn more →The Slide Sorter view in PowerPoint shows thumbnails of all your slides in horizontal rows.The view is useful for applying global changes to several slides at once. Also it's useful for deleting and rearranging slides.
Learn moreAgent memory refers to an AI agent's ability to retain and recall information across tasks and sessions. Two types are commonly distinguished: short-term memory, which holds context within a single agent loop interaction, and long-term memory, which persists across sessions and stores facts, preferences, and historical decisions. Memory is what transforms a stateless AI tool into a context-aware agent that produces increasingly relevant results over time — a core requirement for production Agentic AI deployments.
Learn moreGenerative AI refers to artificial intelligence systems that create new content — such as text, images, code, or structured data — in response to a prompt or task, rather than simply analyzing or classifying existing information. Powered by large language models and other foundation models, generative AI can write documents, summarize reports, produce slide content, and translate data into natural language. In enterprise settings, it is the core technology behind modern AI assistants, document automation tools, and presentation generators.
Learn moreAI orchestration is the coordination of multiple AI agents, tools, and data sources to complete a complex, multi-step workflow. An orchestration layer acts as a conductor: it decides which agent handles which task, in what order, and how outputs are passed between steps — following the same logic as an orchestrator agent. In enterprise communication, AI orchestration enables end-to-end automation — gathering data, structuring content, applying brand guidelines, and publishing a final presentation — all without human handoffs between each stage.
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