Lium, formerly known as Astromind, emerged from stealth and announced the launch of its platform designed to make highly complex datasets accessible through natural language. The company also disclosed that it raised $5.5 million in seed funding from SJF Ventures, Wavemaker 360, Reach Capital, and GC&H Investments.
Founded in 2024, the Dallas-based company enables organizations to interact with challenging datasets, including seismic surveys, satellite imagery, and scientific measurements, using plain English. The platform is designed to provide consistent answers and create institutional knowledge that improves over time.
Lium initially developed its technology through work with astrophysicists analyzing data from NASA’s Chandra X-ray Observatory. Using publicly available mission data, the company made sparse X-ray observations accessible to large language models, helping researchers uncover insights from raw scientific information.
With its commercial launch, Lium is targeting industries where large and fragmented datasets are central to operations and discovery, including energy, geospatial analytics, space, engineering, manufacturing, and scientific research. The platform ingests raw datasets, structures them for AI systems, processes information in advance, and creates specialized workflows that enable more reliable analysis while keeping humans involved in the process.
According to the company, the system becomes increasingly effective with each query, creating a growing repository of institutional knowledge and making technical information easier to search, analyze, and share.
Several organizations have already adopted the platform. Industrial power generator services company nexGEN uses Lium to automate electromagnetic spectrum analysis and generate generator health reports. Geoscience software provider Imaged Reality is integrating Lium into its Stratbox platform to help geologists analyze core imagery, well logs, and geological datasets using natural language.
The North Carolina Institute for Climate Studies is also using the platform to process terabytes of publicly available National Oceanic and Atmospheric Administration data from weather stations, radar systems, satellites, ships, and sensors. Researchers can query historical weather conditions, river levels, and storm patterns and receive immediate analysis.
Lium is backed by SJF Ventures, Wavemaker 360, Reach Capital, and GC&H Investments, and focuses on customers operating across energy, climate, infrastructure, and scientific research sectors.
KEY QUOTES:
“Large language models changed how we work with text and code, but they are quite limited when it comes to understanding the data that represents our physical world. AI holds huge potential to solve many of humanity’s most pressing problems, but the most important data across energy, science, and infrastructure remains difficult for existing systems to reason over. Lium helps teams work with their data to get better answers, faster, and to make that a permanent capability. We’ve created the agentic harness purpose built for turning complex data into knowledge.”
Josh Knutson, Co-Founder And CEO, Lium
“In advanced industries, the answers experts need are often hidden across multiple file formats, disconnected systems, and massive datasets that require a data engineer to work with. Lium removes that complexity, making sophisticated analysis as simple as asking a question. We saw the profound impact of this accelerated analysis in our work in astrophysics, and now our customers are seeing the same value.”
Ryan Thill, Co-Founder And President, Lium
“There is so much incredible, complex data in our world that can reveal truths about everything from climate systems to molecular signals. The constraint isn’t access anymore, it’s usability. That is the problem we’re working to solve. Lium is fundamentally reinventing data architecture, moving beyond data lakes and data warehouses to create a living, explorable data universe.”
Ward Vuillemot, CTO, Lium
“Having access to an AI system like Lium allows our scientists to handle the scale and complexity of the data we work with without also having to be software engineers. A user can quickly gain climate or weather risk insights from numerous complex datasets because Lium manages the compute, blends datasets, and navigates disparate file formats for you.”
James Anheuser, Ph.D., Researcher, North Carolina Institute For Climate Studies
