Large Language Model (LLM)

Large Language Model (LLM)

Term explanation

Definition and meaning

A large language model (LLM) is an AI system trained on vast amounts of text data that can understand, generate, and transform language at a human-like level. LLMs power a wide range of applications — from chatbots and writing assistants to automated document creation and data summarization. In enterprise software, LLMs are increasingly embedded into workflows to interpret unstructured data, draft content, and translate information between systems automatically. In contrast, the Large Presentation Model (LPM) is a specialised AI system that orchestrates the entire presentation cycle in an enterprise context.

LIZ AI leverages large language models to intelligently compose and update presentation content — turning raw data and context into structured, on-brand slides without manual writing.

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Other glossary terms

Closed Questions

Closed questions are questions that can be answered with a limited set of responses — most commonly a simple 'yes' or 'no', or a selection from predefined options. They are used to gather specific, factual information quickly and efficiently. In presentations and training settings, closed questions are useful for gauging audience understanding, confirming agreement, or running quick polls. While efficient, they offer little depth and should be balanced with open-ended questions when richer feedback or discussion is needed.

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Internal Preview

An internal preview is a brief statement placed at the start of a new section within a presentation that signals what is coming next. It acts as a mini roadmap within the talk, preparing the audience for the upcoming content and helping them follow the structure. Together with internal summaries, internal previews create a strong narrative skeleton that keeps listeners oriented and engaged, even in presentations that cover multiple distinct topics.

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AI Guardrails

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.

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Presentation Automation

Presentation automation refers to the use of software to automatically create, update, or distribute presentations based on predefined rules, templates, or live data. It eliminates repetitive manual tasks such as copy-pasting figures into slides, reformatting decks for different audiences, or applying brand updates across hundreds of files. Common use cases include automated management reports, investor updates, and sales decks that always reflect the latest numbers.

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