DALLAS, June 10, 2026 (GLOBE NEWSWIRE) — Lium today emerged from stealth and announced the launch of its platform designed to help organizations make sense of complex, hard-to-use data. Lium takes datasets that are most challenging for AI platforms to reason over — such as seismic surveys, satellite imagery, and scientific measurements — and makes them accessible through natural language. Teams can ask questions in plain English, get consistent, reliable answers without relying on manual analysis or brittle models, and then turn that knowledge into institutional memory that improves over time.
Lium, formerly known as Astromind, was founded in 2024 and raised $5.5M in seed funding from SJF Ventures, Wavemaker 360, Reach Capital, and GC&H Investments. The company developed early versions of its technology working with astrophysicists who interpret the data from NASA’s Chandra X-ray Observatory. Using publicly available mission data, it made notoriously sparse X-ray observations queryable for large language models, helping researchers surface physically meaningful insights from raw data.
With its commercial launch, Lium is focused on industries where complex data drives the most important breakthroughs, including energy, geospatial analytics, space, engineering, manufacturing and scientific research. While AI has rapidly changed how we work with digital information, it has yet to meaningfully impact the domains that rely on large and fragmented datasets, especially those concerning physical systems. Lium is built to change that dynamic and unleash AI to define the next wave of discovery.
“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,” said Josh Knutson, co-founder and CEO of Lium. “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.”
With Lium, teams simply connect their datasets and the platform makes them usable for AI. Lium ingests the raw datasets, structures them into a format that AI systems can reliably work with, processes them in advance so queries return consistent results, and codes specialized tools and workflows, with humans in the loop, to extract better insights. Because the intelligence compounds over time, the system becomes smarter with every query. This makes complex data easier to search, analyze, and share across an organization.
“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,” said Ryan Thill, co-founder and president of Lium. “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.”
Organizations across a range of technical fields are already adopting the platform. Industrial power generator services company nexGEN tapped the platform to automate electromagnetic spectrum analysis, turning raw data into consistent generator health reports and replacing a manual process. Geoscience software provider Imaged Reality is incorporating Lium into its analysis workflows, pairing its subsurface interpretation and visualization tools in Stratbox with natural-language analysis to help geologists interactively explore core imagery, well logs, facies tables, and related geological data.
“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,” said Ward Vuillemot, CTO of Lium. “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.”
The North Carolina Institute for Climate Studies (NCICS) is also an early customer, using Lium to process terabytes of publicly-available National Oceanic and Atmospheric Administration (NOAA) data from weather stations, radar, satellites, ships, and sensors. Scientists can now ask questions about river levels, storm patterns, and historical weather conditions and receive instant analysis.
“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” said James Anheuser, Ph.D., Researcher at NCICS. “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.”
For more information, visit https://www.lium.ai/.
About Lium
Lium makes complex data usable. The company’s platform structures technical datasets and makes them accessible through natural language, enabling teams to analyze, understand, and act on information that was previously difficult to use. Lium supports organizations across energy, climate, infrastructure, and scientific research. The company is backed by SJF Ventures, Wavemaker 360, Reach Capital, and GC&H Investments.
