Term explanation
AI grounding is the process of anchoring an AI system's outputs to verified, real-world data rather than relying solely on knowledge encoded during model training. A grounded AI retrieves relevant, up-to-date information from external sources before generating a response. This significantly reduces the risk of AI hallucinations and ensures that outputs are accurate, current, and contextually relevant — a critical requirement for enterprise AI applications where factual reliability is non-negotiable. Grounding is a core technique used in LLM-powered systems.
LIZ AI grounds every presentation in your actual company data. By connecting directly to your enterprise systems, it ensures that every figure, update, and insight in a slide is pulled from a verified source — not generated from memory.
Learn more →Online communication encompasses all forms of information exchange that take place over digital networks — including email, instant messaging, video calls, social media, webinars, and collaborative platforms. It has become the dominant mode of professional communication, enabling global teams to collaborate in real time regardless of location. Online communication introduces unique challenges around tone, response time, information overload, and the loss of non-verbal cues, all of which require deliberate attention to maintain clarity and connection.
Learn moreA .pptm file is a macro-enabled PowerPoint presentation that contains one or more embedded VBA macros in addition to slides with text, images, and formatting. Macros allow presenters to automate repetitive tasks — such as updating data fields or triggering animations — directly within the file. Because .pptm files can run executable code, they are treated with caution by security tools and should only be opened from trusted sources.
Learn moreA .potx file is a file which contains, styles, texts, layouts and formatting of a PowerPoint (.ppt) file. It's like a template and useful if you want to have more than one presentation with the same formatting.
Learn moreChain of thought is an AI reasoning technique in which a model explicitly works through intermediate steps before arriving at a final answer. By laying out its reasoning step by step, the model produces more accurate and reliable outputs — especially for complex, multi-part problems. In agentic AI systems, chain-of-thought reasoning is used to plan workflows and make decisions at each stage of an agent loop. For enterprise applications, it increases transparency and makes AI behavior easier to audit.
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