Environmental intelligence data spans oceans, geomagnetism, gravity, the atmosphere and ionosphere, and even space-radiation. Data originates from satellites, remote sensing, ground stations, and physics models. Many teams need historical or forecast data for engineering, operations, and compliance.

Our web Application Programming Interfaces remove the integration burden. Instead of stitching together data from disparate sources, software developers connect using a standard interface and start using the data within minutes. This accelerates product development and operational deployment. See our offerings below.

Large Language Model & Retrieval Augmented Generation (RAG+LLM) solutions fuse enterprise documents with predictive Earth intelligence data to produce deeper, operationally useful insights. Internal reports, procedures, specifications, logs, and plans are indexed and retrieved alongside live or historical ocean, geomagnetic, gravity, atmospheric, and radiation data. This gives the model both organisational context and scientific context, allowing it to answer questions with precision instead of speculation.

Our LLM+RAG layer provides the retrieval pipelines, data connectors, and model tooling needed to analyse these combined datasets. The LLM becomes an analytical engine: interpreting documents, correlating them with real-world environmental conditions, and generating actionable assessments for engineering, compliance, and operational planning. This removes the need to assemble a bespoke RAG stack—teams can deploy powerful, domain-specific assistants immediately. See our free offerings below.