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Exploring Earth observation data, such as that managed by NASA, represents a huge challenge even for specialists. With thousands of datasets and tools available, locating the precise resource for a specific investigation can take hours or days. This is where agentive search, powered by artificial intelligence and knowledge graphs, makes a radical difference. This approach not only interprets natural language queries, but combines supervised models with reasoning from large language models (LLMs) to reorder results and dramatically improve accuracy. The key lies in leveraging the semantic richness of a knowledge graph —such as the NASA EO-KG— and complementing it with AI agents capable of reasoning without additional training, achieving 28% increases in metrics like MRR on representative sets.
For companies working with large volumes of geospatial data or any technical domain, this paradigm is directly applicable. Building similar systems requires deep expertise in custom applications that integrate semantic search engines, knowledge bases, and language models. At Q2BSTUDIO we develop custom software that enables organizations to implement intelligent search engines capable of understanding the context of their data. Additionally, we combine AI for businesses with AWS and Azure cloud services to deploy scalable, secure, and high-performance solutions. Our AI agents not only retrieve information, but reason about it, something essential in environments where decision-making depends on cross-referencing multiple sources.
The complementarity between supervised retrieval (such as BM25 combined with a fine scorer) and zero-shot reranking of LLMs shows that a huge model trained from scratch is not needed; it is enough to orchestrate the pieces well. This aligns with our vision of offering business intelligence services that transform data into actionable knowledge. For example, using Power BI we can visualize the results of agentive searches, and with cybersecurity tools we ensure sensitive information is protected. Ultimately, agentive search for Earth observation data is just one example of how the combination of graphs, LLMs, and intelligent software design can revolutionize information accessibility in any sector.
