Deep Tech

The Startups Building the Machines That Could Work the Moon

Getting to the Moon was the first chapter. Interlune and Astrolab are working on how to operate there.

Updated

March 6, 2026 1:32 AM

Apollo 17 Astronaut's Snapshot of Taurus-Littrow Valley. PHOTO: UNSPLASH

As plans for a long-term human presence on the Moon pick up pace, the focus is shifting from landing there to working there. It is one thing to reach the surface. It is another to build roads, prepare sites and extract materials in a way that can support real activity.

That is where Interlune and Astrolab come in. Interlune is a space resources company. Astrolab builds planetary rovers. The two are now working together to mount Interlune’s lunar digging system onto Astrolab’s Flexible Logistics and Exploration (FLEX) rover. They have completed a concept study and are planning hardware testing in Houston.

The aim is straightforward: combine a rover that can move reliably across the Moon with equipment that can dig, collect and handle lunar soil. Interlune is focused on harvesting natural resources from the Moon, starting with helium-3. To do that at scale, the system cannot sit in one place. It has to move across the surface, handle dust and operate in harsh conditions. "Reliable, autonomous mobility is crucial to the Interlune harvesting system and broader lunar infrastructure development", said Rob Meyerson, co-founder and CEO of Interlune. "Astrolab's FLEX is the right vehicle for the job".

By fitting its digging and collection hardware onto FLEX, Interlune is working toward a mobile system that can gather large amounts of lunar soil and support future construction needs. Beyond helium-3, the same setup could help prepare base sites, level ground, build protective barriers and lay the groundwork for other structures. In simple terms, it is about turning a rover into a working machine for the Moon.

The partnership also connects to Interlune’s work with Vermeer Corporation to develop equipment for continuous, high-volume digging adapted to lunar conditions. Taken together, the goal is to build systems that can support both commercial and government missions — whether that means resource extraction or preparing land for future bases.

For Astrolab, the collaboration strengthens the role of FLEX as more than just a transport vehicle.

"Working with Interlune further differentiates FLEX as the rover of choice for commercial and government Moon missions", said Jaret Matthews, Astrolab founder and CEO. "Interlune's expertise in developing and testing highly specialized regolith simulant will further enhance FLEX's ability to mitigate dust and operate in extreme environments".

Testing will be centered in Houston, which is becoming an important hub for commercial space development. Astrolab was the first company to lease space at the Texas A&M University Space Institute, currently under construction at NASA’s Johnson Space Center. Interlune operates the Houston-based Interlune Research Lab, where it creates and tests simulated versions of lunar soil.

That detail matters. Moon dust is fine, abrasive and difficult to manage. Before any hardware flies, it needs to prove it can survive and function in those conditions. By testing their systems in realistic soil simulants, the companies can refine how the rover moves and how the digging system performs.

The Houston lab is partially funded by the Texas Space Commission, reflecting the growing role of regional space initiatives in supporting private companies building beyond Earth. Overall, the collaboration is not about grand promises. It is about integrating hardware, running real tests and taking practical steps toward operating on the Moon.  

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Artificial Intelligence

Inside Botipedia: INSEAD’s AI Breakthrough That Could Redefine How We Access Information

From information gaps to global access — how AI is reshaping the pursuit of knowledge.

Updated

January 8, 2026 6:33 PM

Paper cut-outs of robots sitting on a pile of books. PHOTO: FREEPIK

Encyclopaedias have always been mirrors of their time — from heavy leather-bound volumes in the 19th century to Wikipedia’s community-edited pages online. But as the world’s information multiplies faster than humans can catalogue it, even open platforms struggle to keep pace. Enter Botipedia, a new project from INSEAD, The Business School for the World, that reimagines how knowledge can be created, verified and shared using artificial intelligence.

At its core, Botipedia is powered by proprietary AI that automates the process of writing encyclopaedia entries. Instead of relying on volunteers or editors, it uses a system called Dynamic Multi-method Generation (DMG) — a method that combines hundreds of algorithms and curated datasets to produce high-quality, verifiable content. This AI doesn’t just summarise what already exists; it synthesises information from archives, satellite feeds and data libraries to generate original text grounded in facts.

What makes this innovation significant is the gap it fills in global access to knowledge. While Wikipedia hosts roughly 64 million English-language entries, languages like Swahili have fewer than 40,000 articles — leaving most of the world’s population outside the circle of easily available online information. Botipedia aims to close that gap by generating over 400 billion entries across 100 languages, ensuring that no subject, event or region is overlooked.

"We are creating Botipedia to provide everyone with equal access to information, with no language left behind", says Phil Parker, INSEAD Chaired Professor of Management Science, creator of Botipedia and holder of one of the pioneering patents in the field of generative AI. "We focus on content grounded in data and sources with full provenance, allowing the user to see as many perspectives as possible, as opposed to one potentially biased source".

Unlike many generative AI tools that depend on large language models (LLMs), Botipedia adapts its methods based on the type of content. For instance, weather data is generated using geo-spatial techniques to cover every possible coordinate on Earth. This targeted, multi-method approach helps boost both the accuracy and reliability of what it produces — key challenges in today’s AI-driven content landscape.

Additionally, the innovation is also energy-efficient. Its DMG system operates at a fraction of the processing power required by GPU-heavy models like ChatGPT, making it a sustainable alternative for large-scale content generation.

By combining AI precision, linguistic inclusivity and academic credibility, Botipedia positions itself as more than a digital library — it’s a step toward universal, unbiased access to verified knowledge.

"Botipedia is one of many initiatives of the Human and Machine Intelligence Institute (HUMII) that we are establishing at INSEAD", says Lily Fang, Dean of Research and Innovation at INSEAD. "It is a practical application that builds on INSEAD-linked IP to help people make better decisions with knowledge powered by technology. We want technologies that enhance the quality and meaning of our work and life, to retain human agency and value in the age of intelligence".

By harnessing AI to bridge gaps of language, geography and credibility, Botipedia points to a future where access to knowledge is no longer a privilege, but a shared global resource.