Term explanation
Fundraising events are organized activities designed to generate financial support for a cause, organization, or project. They can take many forms — galas, charity auctions, run events, crowdfunding campaigns, or donor presentations. Effective fundraising events combine compelling storytelling with clear calls to action, making it easy and emotionally motivating for attendees to contribute. The presentation of impact data, beneficiary stories, and organizational credibility is central to converting attendee interest into donations.
LIZ AI helps fundraising teams present with maximum impact. Pitch decks and impact presentations are automatically updated with current figures, case studies, and brand-compliant visuals — ready for every donor meeting.
Learn more →Flipped Classroom means that students work out the subject matter themselves at home through tasks such as reading, videos, etc. Interactive learning activities and exercises then take place in class.
Learn moreA multi-agent system is a setup in which several autonomous AI agents work together, each handling a specific part of a larger task. The agents can communicate, divide work, and combine their outputs to achieve goals that would be difficult for a single model. Typically, an orchestrator agent coordinates the workflow while specialist agents execute defined subtasks. In enterprise contexts, multi-agent systems allow complex workflows — such as researching a topic, drafting content, checking compliance, and distributing a presentation — to be fully automated.
Learn moreA tutorial is a structured learning resource that guides a learner step by step through a process, concept, or skill. Tutorials can take many forms — written guides, video walkthroughs, interactive modules, or one-on-one coaching sessions. Unlike formal courses, tutorials tend to be focused on practical application, helping learners achieve a specific outcome quickly. They are widely used in software onboarding, technical training, and skill development platforms.
Learn moreThe agent loop is the core operating cycle of an autonomous AI agent. It runs continuously through four phases: Perception (gathering information), Reasoning (planning the next step), Action (executing — such as calling a tool or generating content), and Observation (evaluating the result). The loop repeats until the task is complete or the agent requires human input. This is the mechanism behind Agentic AI systems — it is what allows agents to handle complex, multi-step tasks that a single prompt-and-response model could not.
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