Spokesperson: Alexis Cathalifaud, CEO
As demand for synthetic intelligence compute continues to develop, the infrastructure supporting that demand is changing into a strategic consideration in its personal proper. Firms throughout the sector are racing to safe entry to more and more highly effective GPUs, whereas questions round electrical energy, data-center capability, cooling and connectivity have gotten more durable to separate from the compute itself.
Clichmont is taking a distinct strategy. Slightly than constructing its mannequin primarily round rented GPU capability, the corporate is targeted on proudly owning and controlling the bodily infrastructure on which successive generations of AI {hardware} can function. On this interview, Clichmont CEO Alexis Cathalifaud discusses why the corporate believes energy and data-center infrastructure may grow to be the extra sturdy bottlenecks, the way it approaches website choice and the challenges of scaling bodily infrastructure, in addition to the position of its $CLAI token inside the broader ecosystem.
1) Each firm on this class is combating over GPU entry proper now. Clichmont’s reply is to construct the info facilities as an alternative of renting the chips. Why does possession matter greater than entry?
As a result of GPU entry provides you compute; infrastructure possession provides you management over the economics of compute.
For an organization like Clichmont, proudly owning or controlling the data-center layer can matter extra strategically than merely securing rented GPUs. Whenever you hire GPU capability from a hyperscaler or GPU cloud, you inherit another person’s pricing, availability, energy constraints, networking structure, deployment schedule, and margins. When demand spikes, entry can grow to be costly or constrained.
Proudly owning the infrastructure adjustments the equation. Clichmont can probably determine which GPUs to deploy, when to improve them, how densely to put in them, how energy and cooling are engineered, and the way the capability is commercialized. The identical facility also can evolve from one GPU era to the subsequent slightly than tying the enterprise thesis to a selected chip.
There’s one other necessary distinction: GPUs depreciate shortly; power-ready data-center capability is a longer-lived strategic asset. A GPU era might grow to be economically much less aggressive inside a couple of years, whereas land, grid connections, substations, cooling infrastructure, fiber connectivity and permitted megawatts can stay beneficial throughout a number of generations of accelerators.
That makes the scarce useful resource more and more not simply the GPU itself, however the power to energise 1000’s of GPUs at scale. An organization can purchase chips and nonetheless have nowhere appropriate to deploy them. Securing 10,000 GPUs is one downside; securing the tens of megawatts of dependable electrical energy, cooling and community infrastructure required to function them is one other.
2) You’re up towards firms which can be already public or heading there – CoreWeave, Crusoe, Lambda. What do you suppose their mannequin will get incorrect, if something?
I don’t suppose CoreWeave, Crusoe or Lambda acquired the mannequin incorrect. They proved that AI compute is a large market. The place we differ is in what we consider will stay scarce. GPUs change each era. The sturdy bottleneck is the infrastructure required to run them — energy, land, cooling and connectivity. Clichmont’s thesis is that slightly than competing solely to hire the newest GPU, we need to management the infrastructure on which successive generations of GPUs will function. In a market the place everyone seems to be chasing chips, we’d slightly personal the place the place the chips need to dwell
3) There’s a rising argument that vitality, not chips, is the precise bottleneck for AI infrastructure. How a lot does that form the place and the way Clichmont builds?
Vitality shapes nearly each infrastructure resolution we make. A GPU with out dependable energy is simply costly {hardware} sitting in a rack. We consider the actual competitors over the subsequent decade gained’t merely be for GPUs—it is going to be for megawatts.
So when Clichmont evaluates a website, we don’t begin by asking the place we will discover the most cost effective constructing. We ask: the place can we safe dependable energy, on the proper economics, with the power to scale? What’s the time-to-power? What’s the grid scenario? What cooling structure does the local weather permit? And might that website assist the subsequent era of GPUs, not simply those we’re putting in as we speak?
That’s one purpose areas with sturdy vitality fundamentals are strategically attention-grabbing to us. Chips may be shipped around the globe. You’ll be able to’t ship 100 megawatts. The compute finally has to go the place the vitality is.
So I wouldn’t say chips cease being a bottleneck. They continue to be essential. However more and more, proudly owning GPUs isn’t sufficient. The aggressive benefit is with the ability to energy, cool and function them economically at scale. That’s what we’re constructing Clichmont round.
4) Clichmont’s websites vary from a solar-powered facility in Alicante to a brand new construct in Bodo, Norway. What really decides the place a knowledge heart will get constructed – is it about vitality, land, local weather, one thing else?
We don’t select a location as a result of one variable appears enticing. We select it as a result of the complete infrastructure equation works.
Energy is the primary filter: what number of megawatts can we safe, at what price, how dependable is that provide, and—critically—how shortly can it really be delivered? Then we have a look at cooling, local weather, fiber connectivity, land, allowing, safety and the power to increase.
Bodø and Alicante are attention-grabbing exactly as a result of they characterize completely different strengths. Northern Norway provides us a local weather that may assist environment friendly cooling and a powerful vitality setting. Alicante provides us a distinct vitality profile and the chance to combine photo voltaic into the infrastructure technique. We don’t consider each Clichmont knowledge heart must look similar—the structure ought to reply to the sources of the placement.
And land by itself isn’t significantly beneficial to us. An inexpensive parcel with no scalable energy or fiber will not be a data-center website. What issues is whether or not we will flip that location into dependable, economically aggressive compute capability.
In the end, we’re probably not on the lookout for land. We’re on the lookout for locations the place vitality, connectivity, cooling and scalability converge. That’s the place we construct.
5) That is an infrastructure firm with a token connected to it. For a reader who’s skeptical of that mixture, what’s the trustworthy case for why $CLAI exists in any respect?
The skeptical view is totally truthful. A token shouldn’t exist simply because an organization operates in AI. If $CLAI had been merely a financing wrapper round our knowledge facilities, I wouldn’t contemplate {that a} compelling purpose to create it.
Clichmont is the infrastructure enterprise. It builds and operates compute capability. $CLAI is meant to be a digital financial layer across the broader ecosystem — one thing that may finally assist on-chain participation, treasury exercise and neighborhood governance in ways in which standard fairness isn’t designed to do.
And now we have to earn the correct to make that distinction. The bodily infrastructure has to exist independently of the token, and the token has to exhibit actual utility independently of hypothesis. If we will’t present each, then the skepticism is justified.
So I wouldn’t ask anybody to consider in $CLAI just because Clichmont owns GPUs or builds knowledge facilities. The take a look at is way less complicated: does the token finally do one thing helpful, clear and measurable that couldn’t be completed as successfully with a standard database or standard company construction? That’s the usual we ought to be held to.
6) What’s the toughest a part of scaling bodily infrastructure that individuals who’ve solely constructed software program are likely to underestimate?
The toughest half is that bodily infrastructure doesn’t scale at software program pace. In software program, if demand doubles, you possibly can typically provision extra capability shortly. In a knowledge heart, each extra megawatt has a bodily dependency behind it — grid capability, transformers, switchgear, cooling, fiber, permits, building and finally {hardware}.
And people dependencies don’t transfer in parallel as neatly as individuals think about. You’ll be able to have the land and never have the ability. You’ll be able to have the ability allocation and wait months for electrical tools. You’ll be able to have the constructing prepared and nonetheless be ready for a grid connection. One lacking part can delay a complete deployment.
The opposite distinction is that errors are costly and tough to reverse. Software program may be patched in a single day. You’ll be able to’t patch a badly designed 50-megawatt electrical system in a single day. You’re making capital choices as we speak based mostly on what GPUs, energy densities and cooling necessities might seem like a number of years from now.
So the actual talent isn’t merely constructing knowledge facilities. It’s sequencing capital, energy, building and buyer demand in order that they arrive at roughly the identical second. Construct too early and you’ve got costly idle infrastructure. Construct too late and the shopper goes some place else.
That execution self-discipline might be what individuals coming purely from software program underestimate most. In bodily AI infrastructure, pace issues — however timing issues much more.
7) Should you needed to identify the most important danger in betting on a build-it-yourself mannequin as an alternative of a capital-light rental mannequin, what wouldn’t it be?
The largest danger is capital depth mixed with timing. Whenever you construct infrastructure your self, you’re committing vital capital as we speak towards assumptions about demand, energy economics and know-how a number of years into the long run.
A rental mannequin provides you flexibility. If the market adjustments, you possibly can scale back capability, transfer suppliers or undertake the subsequent era of {hardware}. Whenever you personal the infrastructure, you don’t have that luxurious. A substation, cooling system or data-center constructing is a long-duration resolution.
For us, the most important hazard subsequently isn’t merely spending an excessive amount of — it’s constructing the incorrect capability, within the incorrect place, on the incorrect time. Should you construct forward of demand, capital sits idle. Should you construct too slowly, you miss the market.
That’s why we don’t view possession as ‘construct every thing ourselves.’ The target is to manage the strategic infrastructure whereas remaining versatile round know-how. The constructing, energy, cooling and connectivity ought to survive a number of generations of GPUs slightly than changing into depending on one {hardware} cycle.
So sure, the capital-light mannequin has an actual benefit: optionality. Our guess is that if we execute appropriately, giving up some short-term optionality creates one thing extra beneficial over the long run — management over capability, energy economics and the bodily infrastructure that AI more and more is determined by.
8) Three years from now, the place would you like Clichmont to take a seat relative to the CoreWeaves and Nebiuses of the world?
Three years from now, I don’t anticipate Clichmont to be the most important firm within the class, and that’s not the target. CoreWeave and Nebius have huge scale and entry to capital. Attempting to copy them could be the incorrect technique for us.
I need Clichmont to be acknowledged as one of the crucial environment friendly unbiased AI infrastructure operators in Europe — with actual working belongings, secured energy, high-density GPU capability and a observe report of bringing new compute on-line shortly.
Our benefit has to return from being disciplined about the place we construct and what we personal. We would like areas the place the vitality economics make sense, infrastructure designed round successive generations of accelerated computing, and the pliability to serve enterprise AI, HPC and personal compute slightly than merely competing for GPU rental quantity.”
If CoreWeave and Nebius are constructing hyperscale AI clouds, Clichmont can occupy a distinct place: a targeted proprietor and operator of compute-ready infrastructure in strategically chosen markets.
Conclusion
Clichmont’s technique finally comes right down to a long-term infrastructure guess: that entry to GPUs will stay necessary, however the skill to energy, cool, join and function these GPUs effectively at scale will grow to be an more and more beneficial benefit.
That strategy comes with significant trade-offs. Constructing bodily infrastructure requires substantial capital, lengthy planning horizons and cautious coordination between energy, building, {hardware} and demand. Clichmont’s thesis is that accepting these constraints can present better management over the infrastructure required for successive generations of AI compute. Whether or not that thesis proves out will rely much less on the ambition of the mannequin than on the corporate’s skill to execute it effectively and on the proper time.
