In a recent interview at the Data Day Texas conference in Austin, Alexy and Claire Sullivan chatted about her journey as a freelance data scientist. Claire shared insights into her diverse career path, which began in nuclear engineering before transitioning into data science and AI. Her experience at GitHub introduced her to graph technology, ultimately leading her to Neo4j, where she became a key advocate for graph-based data science. Now running her own company, Claire reflected on how advancements in generative AI and graph databases have transformed the field, making tasks that were once complex far more accessible. She highlighted how knowledge graphs and vector-based retrieval are becoming essential tools for AI applications, emphasizing the growing role of graphs in shaping the future of artificial intelligence.

Throughout the conversation, Claire also touched on the challenge of educating developers and businesses about graph technology. Many still associate graphs with charts rather than the powerful data structures that underpin modern AI applications. She stressed the importance of meeting developers where they are, simplifying complex concepts, and showing the real-world impact of graph-based approaches. Claire’s enthusiasm for the field was evident as she discussed the energy of the Data Day Texas community, where practitioners openly share insights and practical experiences. As graph technology continues to gain traction, Claire’s perspective reinforced the idea that the key to broader adoption lies in clear communication, hands-on learning, and demonstrating tangible benefits to AI-driven workflows.

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