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Scaling Secrets

Scaling Secrets

Entrepreneur09-05-2025

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Scaling a business is one of the most challenging yet exciting feats for any entrepreneur. It requires a delicate balance between maintaining quality, building a strong culture, managing operational hurdles, and adapting to ever-evolving customer needs. To uncover the secrets to scaling successfully, Entrepreneur UK spoke to three leaders who have navigated this path: Lauren Chiren, CEO of Women of a Certain Stage, Richard Robinson, CEO at Robin AI, and Griffin Parry, CEO of m3ter. Here's how they scaled their businesses effectively without losing sight of what made them unique.
Building the foundation
For Lauren Chiren, scaling was all about establishing a repeatable foundation without compromising the quality of service her business offers. "From the start, I focused on documenting systems and processes that worked - everything from client onboarding to delivery standards and follow-up procedures," she explains. By creating clear, repeatable processes, Chiren was able to quickly scale her operations and train new team members efficiently, ensuring consistent quality even as demand increased. But growth doesn't happen overnight. Lauren advises adopting a "lean scaling" approach, where businesses grow in stages. "We tested each new program or service in a smaller setting before rolling it out more widely," she shares. This approach allowed her team to troubleshoot potential challenges early on and maintain high standards of service, whether in menopause education or hygiene services. As Chiren points out, "Culture doesn't happen by accident—it's something you have to cultivate intentionally." And her team was grounded in values like integrity, compassion, and professionalism. This deep commitment to core principles helped ensure that her company's growth was not just rapid but also sustainable.
Pace over speed
Richard Robinson of Robin AI also emphasises a strategic approach to scaling, focusing on maintaining the pace rather than rushing for speed. "We preach pace over speed. We want to always be moving forward, but not at any cost," he shares. As an AI company, Robinson has to balance innovation with security and reliability. "We have to prioritise safety and security in our AI. We work hard to use tech where we can, like managing a global team with different legal obligations depending on their location." In addition to ensuring that the right technology and tools are in place, Robinson takes a hands-on approach to culture-building by maintaining open communication. "We run open-plan offices, with regular all-hands meetings. I sign-off on all new hires, and for senior hires, I interview them myself." The hands-on culture has played a vital role in ensuring quality and cohesiveness even as the company expanded rapidly. However, operational challenges did arise. "We reached a point where most of our revenue was coming from the US but our brand awareness didn't reflect that," Robinson explains. He quickly identified that the solution was showing up—attending major events and engaging with tech and legal communities to increase visibility in the U.S.
Being deliberate: Cultivating culture and operational systems
For Griffin Parry, CEO of m3ter, maintaining a high quality of service while scaling required a methodical approach. "I think of building a company as solving a series of problems in the right sequence and at the right cadence," he says. The challenges are seen as "brain teasers," and scaling is about addressing each one carefully to ensure smooth growth. A major challenge, according to Parry, is maintaining culture and quality as the team grows. When you're small, it's easy to ensure that every team member is aligned with the company's mission. However, that becomes difficult as you expand. "The answer is to rely on mechanisms rather than good intentions," he suggests. Parry emphasises that the key to successful scaling is being deliberate about culture. "You can't impose culture, but you can deliberately cultivate it," he notes. At m3ter, they hired a People leader early on, creating systems and processes that embedded the company's values. These efforts helped cultivate a strong company culture that the entire team could take ownership of, ensuring that the company remained cohesive despite rapid growth.
Customer acquisition vs. retention: Striking the right balance
As these entrepreneurs scaled their businesses, they faced the challenge of striking a balance between acquiring new customers and retaining existing ones. Parry optimises for customer satisfaction and retention. "We're a recurring revenue business, and it's cheaper to keep customers than win them," he says. At m3ter, this focus on retention has not only resulted in a loyal customer base but has also led to product improvements. For example, their "Robin Reports" feature was co-developed with the University of Cambridge to meet specific needs. Parry shares, "We couldn't have done that without close relationships with that customer." Similarly, Robinson believes in a flexible pricing model that ensures customer satisfaction. "We don't get customers complaining about paying for services they didn't use," he explains. Robinson's approach involves working closely with customers to develop new features and continuously improve their offerings.
Strategic expansion: Narrow focus for greater success
When it comes to expanding into new markets, both Robinson and Parry emphasise being strategic and deliberate. Parry advocates for going "uncomfortably narrow" with your Ideal Customer Profile (ICP). "Be very specific about who you want to sell to and why you're the best option for them," he advises. It may take longer in the short term, but it leads to a stronger, more engaged customer base in the long run. Robinson also focused on geographical expansion to the US where he identified a gap in brand awareness. His strategy included attending major events and building relationships within legal and tech communities. This type of "showing up" has helped Robin AI scale globally.
Lastly, the entrepreneurs also weighed in on how UK trade policies have influenced their ability to expand internationally. For Chiren, the post-Brexit landscape posed challenges when working with global clients. While UK trade policies supported exports, navigating different tax and legal frameworks added complexity. Similarly, Parry cited the UK's favorable policies around EIS/SEIS tax breaks and R&D tax credits as key factors that have supported m3ter's growth. However, Robinson noted that Brexit has made European expansion more challenging, while also highlighting the success of trade mission programs run by successive UK governments, particularly in the US and Asia.
Scaling smartly for long-term success
The road to scaling a business is filled with challenges, but these entrepreneurs demonstrate that with the right strategies - be it a focus on repeatable processes, a commitment to culture, deliberate expansion, or the balance of customer acquisition and retention—you can navigate those challenges effectively. As they scale, they remain grounded in their mission, ensuring that growth is sustainable, aligned with values, and focused on the long-term goal. Scaling isn't just about growing fast; it's about growing smart. It's this intelligent approach that enables entrepreneurs to scale their businesses without compromising quality.

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This 45% discount is meaningful, and such a price difference can be very compelling for cost-sensitive customers like AI startups burning investor cash to train models. Source: CoreWeave Interestingly, both companies count NVIDIA as a strategic backer. NVIDIA invested $350 million for a 7% stake in CoreWeave and also participated in Nebius's funding round. This dual alignment signals NVIDIA's intention to support multiple GPU-native cloud providers and maintain high downstream demand for its hardware. That backing also gives both firms early access to next-gen chipsan edge in securing performance-sensitive workloads. Neither Nebius nor CoreWeave builds its own chips (unlike AWS with Trainium or Google with TPUs), but both are innovating in deployment. Nebius, for instance, secured early access to Blackwell GPUs in Europe, likely aided by its speed of execution and strategic positioning. Similarly, CoreWeave was among the first to offer H100s at scale in 2023. Both aim to stay on the bleeding edge of NVIDIA's roadmapand attract customers accordingly. A critical piece of the analysis for any cloud provider is unit economics. How profitable (or not) each unit of service is, and what the cost drivers are. In the context of Nebius and its peers, the unit is often one GPU hour of computation. On the revenue side of a GPU-hour, as noted, Nebius cut its on-demand H100 GPU price to $2.95/hour or even lower with long-term commitments. For comparison, AWS charges around $12.29/hour for an on-demand H100 80GB (depending on region). Now, on the cost side, providing one hour of H100 time involves several components: depreciation or lease costs for the GPU hardware, electricity, cooling, infrastructure overhead, and some share of staffing and maintenance. Assuming a $30,000 price tag for an Nvidia H100 80GB and a 3-year capital recovery period, that's $833 per month. At 730 hours/month (247 uptime), that equates to $1.14 per hour just to break even on the hardware. In practice, utilisation isn't 100% (there will be some idle or reserved time), and there are significant power/cooling costs. An H100 can draw 300 to 400 watts under load. At $0.05$0.10 per kWh, electricity costs range from $0.15 to $0.30/hour. Add cooling and networking overhead ($0.10/hour), and total operational costs sit between $0.20 and $0.40/hour. Server CPUs, memory, and networking per GPU add further costs, though relatively minor on a per-hour basis. Bringing this together: if Nebius averages $2.20/hour per H100 (blended between on-demand and committed use) and runs at 80% utilisation, it generates $1.76/hour. With $0.32 in variable opex and $1.14 in depreciation, that leaves $0.30 of gross margin per available hour. Over a year (8,760 hours), this adds up to $15,400 in revenue and $12,600 in gross cash flow, enough to recoup the GPU investment in just under 2.5 years, excluding staff and overhead. At CoreWeave's $4.25/hour, the math looks different. At 80% utilisation, it earns $3.40/hour, about $22,500 annually per GPU. That allows for a 1.3-year payback, assuming similar cost assumptions. But I would expect the higher price tag may reduce utilisation. From a capex efficiency standpoint, Nebius may have structural advantages. First, its balance sheet: it holds $1.4 billion in net cash, while CoreWeave carries $6.2 billion in net debt. CoreWeave's debt-servicing costs add to its effective GPU-hour cost. Second, Nebius can build where costs are lowest. For example, its Finnish data centre benefits from ambient air cooling and access to low-cost nuclear and hydro power. Finland's industrial electricity rates (0.05 to 0.07/kWh) are highly competitive, even versus many U.S. regions. Further Nordic or Eastern European expansion could enhance this edge. Crusoe, for example, takes this to the extreme, placing data centres at oil wells to tap into otherwise flared gas. Another factor in unit economics is utilization rate. One challenge for Nebius is to attract enough workloads to keep tens of thousands of new GPUs busy. However, the company's latest disclosures show extremely strong uptake. By April 2025, Nebius's Annualized Run-Rate Revenue (ARR) reached $310 million, up from $249 million in March. This implies that newly added GPUs were getting filled with work rapidly. Nebius's ARR was growing 684% year-on-year (YoY) as of Q1 2025, indicating that as soon as Nebius deploys more capacity (e.g., a new cluster online), it's seeing customers take it up, likely attracted by the combination of availability and price. GPU mix also plays a role. While H100s are the flagship, Nebius offers older and mid-range GPUs too, like A100s, L40s, or A10s. Many of these were acquired second-hand from miners. A GPU like the A10, which costs $3,500, might rent at $0.75/hour. At 80% utilisation, it brings in $5,200/year, allowing the investment to be recouped in less than 12 months. These legacy GPUs offer higher ROI and subsidise thinner margins on cutting-edge chips. CoreWeave and Lambda Labs use similar strategies. Older GPUs like the A6000 or RTX 3090 have long since paid for themselves, but still rent out at attractive rates. These high-margin units improve blended economics and cushion the break-even curve on H100s or Blackwells. Nebius's revenues are starting from a relatively small base but are growing at an extraordinary pace. In Q1 2025, the company reported revenue of $55.3 million, up 385% year over year, while ARR surged nearly 700% YoY, reaching $310 million by April 2025. This growth, however, comes at a cost: Nebius remains in investment mode and is still loss-making as it builds out infrastructure. In Q1 2025, it posted an adjusted EBITDA loss of $62.6 million and a net loss from continuing operations of $113.6 million. That's wider than the $80.5 million loss in the same period last year, driven by increased operating expenses and depreciation. Still, there are early signs of operating leverage: opex as a percentage of revenue improved from an unsustainable 827% in Q1 2024 to 334% in Q1 2025, an indication that Nebius is gaining scale efficiency even as absolute costs rise. Cash burn remains high. Operating cash outflow reached $197.8 million in Q1 2025 alone. But Nebius's balance sheet is strong. It holds $1.5 billion in cash and cash equivalents against just $6.2 million in debt, providing a solid funding runway. Management has guided for full-year 2025 revenue of $500 to $700 million, potentially 5 higher than 2024 levels, with ARR approaching $1 billion. Longer term, the company targets a 30% adjusted EBIT margin, with room for additional upside as utilisation and gross margins improve. When Nebius re-listed on Nasdaq in October 2024, shares initially traded around $20, giving the company a market capitalization of roughly $4 billionabout where Yandex N.V. had been pre-suspension. At that price, with 2024 revenue at $118 million, Nebius was valued at an eye-watering 34 trailing price-to-sales (P/S). Even on a forward basissay, $600 million in projected 2025 revenue, that implied a 7 forward P/S. A modest multiple for a company growing at 400%+. Investors, drawn by the company's hypergrowth and AI focus, quickly bid up the stock in 2025. Today, Nebius trades at $47, giving it a market cap of $11 billion. At this price, the forward P/S climbs to 18. The EV/Revenue multiple is slightly lower, thanks to Nebius' $1.5 billion in net cash, which brings enterprise value down to $9.7 billion, equating to 16 2025E revenue. Another lens is ARR. At $310 million in April 2025, Nebius trades at 35 ARR. This multiple reflects the market's expectation of sustained exponential growth, justified, to some extent, by its 684% YoY ARR growth at last disclosure. CoreWeave, by comparison, has $2.7 billion in trailing revenue and is valued at around $71 billion, implying a trailing P/S of 26 and a forward P/S closer to 14. GPU count provides another useful valuation reference. Nebius currently has 30,000 GPUs and plans to add up to 60,000 in Finland and another 35,000 in Kansas City. At today's EV, that works out to $324,000 per GPU. CoreWeave, with an enterprise value of $76.9 billion and 250,000 Blackwell GPUs allocated, trades at $307,000 per GPU. On a per-GPU basis, Nebius looks slightly more expensive. However, that spread may be justified by Nebius's capital structure. Unlike CoreWeave, which is heavily levered, Nebius is deploying GPUs primarily through cash, implying less financial risk and potentially better long-term margins. In that context, investors could rationally pay more per GPU for Nebius. It's also worth noting: this valuation assumes Nebius's market cap reflects only its AI Studio business. If you assign any value to Toloka, TripleTen, or Avride, Nebius's implied EV per GPU drops below CoreWeave's. In that sense, the headline multiple overstates how richly Nebius is valued for its core cloud operations alone. Finally, Nebius isn't just attracting retail momentumseveral institutional investors and well-known funds are getting behind the story. In the most recent quarter, John Hussman (Trades, Portfolio), Jefferies Group (Trades, Portfolio), and Paul Tudor Jones (Trades, Portfolio) all increased their stakes in the company, suggesting rising institutional confidence in Nebius's long-term positioning. While Nebius offers a compelling avenue to participate in the AI compute boom, the path from promise to profit is far from guaranteed. The first hurdle is execution. Scaling the fleet from ~30,000 GPUs to more than 60,000 across Finland, the U.K., and a new U.S. cluster will require flawless logistics, uninterrupted chip supply, and enterprise-grade reliability. That leads into a second, more fundamental concern: utilisation risk. Nebius's economic model depends on sustaining high GPU usagetypically around 80%to make the unit economics viable. But that level of utilisation isn't assured. CoreWeave, AWS, Google Cloud, and niche players like Lambda Labs are all aggressively competing for GPU workloads. Pricing pressure, customer churn, or simple overbuild could impair Nebius's ability to monetise its fleet efficiently. Finally, Investors should also be aware that many view Nebius and its peers as AI compute landlords, by essentially renting GPUs like digital REITs. However, there's a key distinction. While REITs benefit from physical assets that depreciate slowly over decades, GPU hardware becomes obsolete within two to three years. The capital turnover is faster, the risk of stranded assets is higher, and the need to reinvest in cutting-edge chips like Blackwell or H200 is constant. Nebius isn't just another AI infrastructure play. It's a true challenger in a market long dominated by hyperscalers. Its explosive growth, capital-light balance sheet, and global-first strategy set it apart from competitors like CoreWeave and Lambda. It also offers some diversification through its other business segments. While its GPU fleet is smaller for now, Nebius's cost advantages and platform breadth provide a credible path to scale. If management executes and demand for AI compute continues to accelerate, today's $12 billion valuation could prove to be a stepping stone, not a ceiling. Ultimately, the AI gold rush won't reward every miner. The winners will be infrastructure providers that combine scale, capital efficiency, and customer-focused design. Nebius is building toward that vision, and it's already secured a seat at the table. I believe Nebius could be a market-beater over the long term. This article first appeared on GuruFocus. Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data

Nvidia (NVDA) Builds AI Momentum Ahead of Q2 Earnings
Nvidia (NVDA) Builds AI Momentum Ahead of Q2 Earnings

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Nvidia (NVDA) Builds AI Momentum Ahead of Q2 Earnings

Nvidia (NVDA, Financials) may be poised for a breakout to new highs as analysts revise forecasts and global demand for its AI hardware continues to rise. Warning! GuruFocus has detected 4 Warning Signs with NVDA. Wedbush's Dan Ives said chip exports may be back on the table in upcoming U.S.-China trade talks; if true, that could reopen Nvidia's pipeline for H20 GPUs. CEO Jensen Huang remains cautious; however, both he and Ives agree that China already has capable GPU alternatives, particularly through Huawei and those could erode U.S. market share if restrictions persist. Meanwhile, Nvidia continues building momentum abroad. At its GTC Paris event, the company unveiled over 3,000 exaflops' worth of AI compute deals across Europe and the Middle East; the initiative includes gigafactories, localized AI factories, and supercomputing centers. One high-profile collaboration involves Saudi-backed HUMAIN. Nvidia isn't just betting on hardware; it's also backing software. The company recently made a minority investment in robotics startup Skild during a $25 million Series B round; the deal values Skild at nearly $4.5 billion and aligns with Nvidia's long-term play in autonomous systems and industrial AI. With Blackwell deployments expanding, export rules under scrutiny, and new demand surfacing in emerging markets, Nvidia looks set for a pivotal Q2. This article first appeared on GuruFocus.

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