Term explanation
The 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.
LIZ AI uses MCP to connect seamlessly to your enterprise systems — CRM, ERP, BI tools, and more. Through standardized MCP integrations, it retrieves live data and feeds it directly into your PowerPoint presentations, automatically and securely.
Learn more →A persuasive presentation is designed to change the audience's opinion, attitude, or behavior. The presenter builds a case using evidence, logic, and emotional appeal to move the audience toward a specific conclusion or action. Persuasive presentations are common in sales pitches, political speeches, fundraising campaigns, and change management initiatives. They differ from informative presentations in that they take a deliberate position and actively seek buy-in.
Learn moreDiagonal communication means that the employees of a company communicate with each other regardless of their function and their level in the organisational hierarchy and regardless of their department within the company.
Learn morePop-up events are temporary, often spontaneous gatherings organized quickly and held for a limited time in unexpected or unconventional locations. They are used in retail, marketing, arts, and community organizing to create a sense of exclusivity and surprise. Pop-up events require rapid logistics coordination and lean heavily on social media and word-of-mouth for promotion. Their short-lived nature generates urgency and tends to attract higher engagement than regularly scheduled events.
Learn moreAI 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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