Term explanation
A data-driven presentation is a slide deck in which the content — charts, KPIs, tables, and narrative text — is directly derived from live or structured data sources rather than manually entered. Rather than copying figures from a dashboard into PowerPoint, data-driven presentations pull information automatically from connected systems such as CRM, ERP, or BI tools. The result is a living presentation that always reflects current data — and is the foundation of Agentic Slides architecture.
LIZ AI transforms any PowerPoint into a data-driven presentation: it connects directly to your enterprise systems, retrieves the latest figures, and updates slides automatically — so every deck reflects the current state of your business.
Learn more →A solution presentation is a structured pitch in which a presenter proposes a specific product, service, or approach to address a client's problem or business challenge. It typically frames the customer's pain point first, then presents the proposed solution and its benefits, supported by evidence or case studies. Solution presentations are central to B2B sales processes and consulting engagements, where building relevance and credibility is critical to winning the deal.
Learn moreA student response system (SRS) is a technology that allows students to respond to questions or polls during a class or presentation using personal devices or dedicated clickers. Responses are collected and displayed in real time, giving instructors immediate insight into comprehension levels and enabling on-the-spot adjustments to pacing or content. Student response systems improve engagement, reduce passive listening, and make large group instruction more interactive.
Learn moreAI 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.
Learn moreThe Model Context Protocol (MCP) is an open standard developed by Anthropic in 2024 and widely adopted in 2025 by OpenAI, Google, and Microsoft. It defines a standardized way for AI agents to connect to external tools, data sources, and enterprise systems — without requiring custom integrations for every connection. MCP acts as a universal interface: an AI agent with MCP support can securely access databases, APIs, document repositories, and business applications using a consistent protocol, regardless of the underlying system. This dramatically simplifies how AI is embedded into complex enterprise environments.
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