Spokesperson: Alexis Cathalifaud, CEO
As demand for synthetic intelligence compute continues to develop, the infrastructure supporting that demand is turning into a strategic consideration in its personal proper. Corporations 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 tougher to separate from the compute itself.
Clichmont is taking a unique strategy. Fairly than constructing its mannequin primarily round rented GPU capability, the corporate is concentrated 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 might change into the extra sturdy bottlenecks, the way it approaches web site choice and the challenges of scaling bodily infrastructure, in addition to the function of its $CLAI token inside the broader ecosystem.
1) Each firm on this class is preventing over GPU entry proper now. Clichmont’s reply is to construct the info facilities as a substitute of renting the chips. Why does possession matter greater than entry?
As a result of GPU entry offers you compute; infrastructure possession offers 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 change into costly or constrained.
Proudly owning the infrastructure modifications the equation. Clichmont can doubtlessly resolve 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 may evolve from one GPU technology to the following slightly than tying the enterprise thesis to a specific chip.
There’s one other necessary distinction: GPUs depreciate rapidly; power-ready data-center capability is a longer-lived strategic asset. A GPU technology could change into economically much less aggressive inside just a few 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 flexibility 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 in opposition to corporations which might be already public or heading there – CoreWeave, Crusoe, Lambda. What do you assume their mannequin will get mistaken, if something?
I don’t assume CoreWeave, Crusoe or Lambda acquired the mannequin mistaken. They proved that AI compute is a large market. The place we differ is in what we consider will stay scarce. GPUs change each technology. 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 most recent GPU, we wish 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 reside
3) There’s a rising argument that power, not chips, is the precise bottleneck for AI infrastructure. How a lot does that form the place and the way Clichmont builds?
Power shapes nearly each infrastructure resolution we make. A GPU with out dependable energy is simply costly {hardware} sitting in a rack. We consider the true competitors over the following decade gained’t merely be for GPUs—it will likely be for megawatts.
So when Clichmont evaluates a web site, we don’t begin by asking the place we are able to discover the most cost effective constructing. We ask: the place can we safe dependable energy, on the proper economics, with the flexibility to scale? What’s the time-to-power? What’s the grid state of affairs? What cooling structure does the local weather enable? And might that web site help the following technology of GPUs, not simply those we’re putting in immediately?
That’s one motive places with robust power fundamentals are strategically fascinating to us. Chips may be shipped around the globe. You may’t ship 100 megawatts. The compute finally has to go the place the power is.
So I wouldn’t say chips cease being a bottleneck. They continue to be important. However more and more, proudly owning GPUs isn’t sufficient. The aggressive benefit is having 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 truly decides the place an information heart will get constructed – is it about power, land, local weather, one thing else?
We don’t select a location as a result of one variable appears engaging. We select it as a result of all the 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 rapidly can it truly be delivered? Then we take a look at cooling, local weather, fiber connectivity, land, allowing, safety and the flexibility to broaden.
Bodø and Alicante are fascinating exactly as a result of they symbolize completely different strengths. Northern Norway offers us a local weather that may help environment friendly cooling and a powerful power surroundings. Alicante offers us a unique power profile and the chance to combine photo voltaic into the infrastructure technique. We don’t consider each Clichmont knowledge heart must look equivalent—the structure ought to reply to the assets of the situation.
And land by itself isn’t notably beneficial to us. An inexpensive parcel with no scalable energy or fiber just isn’t a data-center web site. What issues is whether or not we are able to flip that location into dependable, economically aggressive compute capability.
Finally, we’re not likely on the lookout for land. We’re on the lookout for locations the place power, connectivity, cooling and scalability converge. That’s the place we construct.
5) That is an infrastructure firm with a token hooked up 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 honest. A token shouldn’t exist simply because an organization operates in AI. If $CLAI have been merely a financing wrapper round our knowledge facilities, I wouldn’t think about {that a} compelling motive 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 help on-chain participation, treasury exercise and neighborhood governance in ways in which typical fairness isn’t designed to do.
And we’ve got to earn the best to make that distinction. The bodily infrastructure has to exist independently of the token, and the token has to show actual utility independently of hypothesis. If we are able to’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 far easier: does the token finally do one thing helpful, clear and measurable that couldn’t be achieved as successfully with a standard database or typical company construction? That’s the usual we needs to be held to.
6) What’s the toughest a part of scaling bodily infrastructure that individuals who’ve solely constructed software program are inclined to underestimate?
The toughest half is that bodily infrastructure doesn’t scale at software program pace. In software program, if demand doubles, you’ll be able to usually provision extra capability rapidly. In an information heart, each further megawatt has a bodily dependency behind it — grid capability, transformers, switchgear, cooling, fiber, permits, development and finally {hardware}.
And people dependencies don’t transfer in parallel as neatly as folks think about. You may have the land and never have the ability. You may have the ability allocation and wait months for electrical tools. You may have the constructing prepared and nonetheless be ready for a grid connection. One lacking element can delay a whole deployment.
The opposite distinction is that errors are costly and tough to reverse. Software program may be patched in a single day. You may’t patch a badly designed 50-megawatt electrical system in a single day. You’re making capital choices immediately primarily based on what GPUs, energy densities and cooling necessities could seem like a number of years from now.
So the true ability isn’t merely constructing knowledge facilities. It’s sequencing capital, energy, development 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 client goes someplace else.
That execution self-discipline might be what folks coming purely from software program underestimate most. In bodily AI infrastructure, pace issues — however timing issues much more.
7) For those who needed to identify the largest threat in betting on a build-it-yourself mannequin as a substitute of a capital-light rental mannequin, what would it not be?
The largest threat is capital depth mixed with timing. Whenever you construct infrastructure your self, you’re committing important capital immediately in opposition to assumptions about demand, energy economics and know-how a number of years into the longer term.
A rental mannequin offers you flexibility. If the market modifications, you’ll be able to scale back capability, transfer suppliers or undertake the following technology 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 largest hazard subsequently isn’t merely spending an excessive amount of — it’s constructing the mistaken capability, within the mistaken place, on the mistaken time. For those who construct forward of demand, capital sits idle. For those who construct too slowly, you miss the market.
That’s why we don’t view possession as ‘construct every little thing ourselves.’ The target is to regulate 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 turning into depending on one {hardware} cycle.
So sure, the capital-light mannequin has an actual benefit: optionality. Our guess is that if we execute accurately, 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 relies on.
8) Three years from now, the place would you like Clichmont to sit down relative to the CoreWeaves and Nebiuses of the world?
Three years from now, I don’t anticipate Clichmont to be the largest firm within the class, and that’s not the target. CoreWeave and Nebius have huge scale and entry to capital. Making an attempt to copy them can be the mistaken technique for us.
I would like Clichmont to be acknowledged as one of the crucial environment friendly unbiased AI infrastructure operators in Europe — with actual working property, secured energy, high-density GPU capability and a monitor report of bringing new compute on-line rapidly.
Our benefit has to come back from being disciplined about the place we construct and what we personal. We wish places the place the power 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 unique 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 potential to energy, cool, join and function these GPUs effectively at scale will change into 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, development, {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 potential to execute it effectively and on the proper time.
