The GenViz whitepaper outlines an AI-driven framework for transforming natural language into effective data visualizations, addressing the rising demand for accessible analytics. Traditional tools require expertise and manual effort, while generative visualization automates chart selection, insight generation, and storytelling. The architecture includes modules for natural language understanding, schema mapping, visualization recommendation, and interactive user interfaces, all supported by LLMs and ML. A data flow pipeline processes queries through these modules to deliver dynamic, personalized visuals. Challenges include ambiguity, scalability, and user trust, but future opportunities lie in proactive, explainable, and multimodal visualizations.

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