SEARCH AI is a tool in development at SBU Libraries designed to help users explore our catalog using natural language queries. Available as a toggle within our catalog webpage, SEARCH AI works by using generative AI to expand upon the topic of interest, dynamically select appropriate filters, and bring the user directly to the search results in our catalog. SEARCH AI went live in beta form in October 2025.
Why SEARCH AI
Getting relevant results from traditional library searches often requires familiarity with Boolean operators and how the catalog works, which can be challenging for many users. We want researchers to be able to find relevant materials to their studies without having to think about the syntax of the search query. Natural language translation to a proper catalog search removes the extra steps needed for individuals to find what it is they are looking for, enhancing discoverability of all our materials. We think SEARCH AI can make our library catalog more approachable, while making the researchers’ work more efficient.
Key features
- Semantic search / natural language queries – Ask questions in plain language.
- Boolean string creation – Generates a set of related keywords for the topic.
- Date range selection – Limit results by creation or publication date.
- Material type filtering – Focus the search on books, articles, dissertations, and more.
- Facet controls – Easily filter by peer-reviewed content, online availability, or items held by SBU Libraries.
Roadmap
SEARCH AI has been used thousands of times by our community since launch in October 2025 with positive feedback from students, faculty, and staff. It has been used as the center for AI research projects by our faculty, and it has recently been nominated for the 2026 Clarivate Library Innovation Awards. We intend to iterate on this tool to provide as much value to the user experience as possible.
Large Language Models (LLMs) and Data Privacy
At the moment, SEARCH AI uses OpenAI large language models to complete searches. The OpenAI model gpt-4.1-nano is used as a baseline model and fine-tuned gpt-4o models are used as agents. Personal information is not included with user queries. Data transmitted to the OpenAI API is not used by OpenAI for training.
Stony Brook Libraries maintains full control of SEARCH AI data and none of the data is used by external parties. In the future, there is potential for SEARCH AI and our projects to run on local AI servers.
Limitations
SEARCH AI uses artificial intelligence to generate responses and assist with information retrieval, but it has important limitations. AI may produce errors, outdated details, or incomplete information. SEARCH AI has these same limitations. Because of this, responses should be treated as a starting point rather than a final authority. Additionally, AI is not appropriate for processing sensitive, private, or personally identifiable information, and its role is to support and not replace human expertise.
If you want to learn more about generative AI, visit the Stony Brook University Library Guide here.
