Term explanation
A 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.
The architecture behind LIZ AI is built on multi-agent principles: specialized agents handle data retrieval, content composition, brand compliance, and distribution — working in concert to deliver complete, production-ready presentations.
Learn more →A motivational presentation is designed to inspire, energize, and encourage the audience to pursue a goal or embrace a change. It relies on storytelling, emotional resonance, and vivid examples to create personal relevance and shift the audience's mindset. Motivational presentations are used at company kick-offs, leadership events, team rallies, and public speaking engagements. Their effectiveness depends heavily on the authenticity and energy of the presenter.
Learn moreFor a manuscript speech, the speaker has an entire manuscript to read from. The benefit is that, as every single word is scripted, no important parts will be missed. However, speeches that are fully written down often seem unnatural and may bore the audience.
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 moreGame-based learning (GBL) uses game mechanics — such as points, levels, challenges, and rewards — to deliver educational content in an engaging format. Games motivate learners through competition, narrative, and immediate feedback, making them particularly effective for skill practice and knowledge reinforcement. Game-based learning ranges from simple quiz games to complex simulations and serious games developed for specific professional training scenarios.
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