How we integrate AI and LLMs to make product data more accessible

At SPREAD, we are committed to making engineering intelligence more intuitive and user-friendly. To take this to the next level, we have integrated Large Language Models (LLMs) into our platform, introducing SPREAD GPT—a powerful AI-driven tool that allows users to query complex product data using natural language.

By combining Knowledge Graphs with LLMs, SPREAD GPT eliminates the need for complex manual queries, enabling engineers to retrieve and analyze data faster. This marks a significant step toward AI-native engineering software, where users can interact with AI-powered product development tools to streamline workflows and unlock insights throughout the product lifecycle.

Looking ahead, we are enhancing SPREAD GPT’s capabilities to dynamically adjust visual representations in response to user queries. This means that engineers will not only be able to ask questions in natural language but also see interactive visualizations of product dependencies, design changes, and failure patterns—further driving efficiency and making product data truly accessible and actionable.

Watch our Senior Product Owner, Daniel Wilms, as he dives deep into the powerful synergy between Knowledge Graphs and LLMs and demonstrates how SPREAD GPT is redefining AI for complex product lifecycle management. Experience the future of AI-native engineering software today.