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Why Neoclouds Matter More Now

AI infrastructure is moving into a phase where access, speed, and cost all tighten at the same time. That pressure is what gave rise to neoclouds, but it’s also what determines whether they hold up.

Demand for compute is not waiting. GPU capacity is claimed early, pricing moves quickly, and the cost of producing tokens is starting to define which companies can operate at scale. That puts pressure on every layer underneath, from silicon supply to how clusters are actually run day to day.

Neoclouds sit directly in that gap. They’re built to move faster than hyperscalers, to bring GPU capacity online quickly, and to offer more flexibility in how that capacity is used. That solves the first problem, which is access. The harder problem starts once that infrastructure is live.

Running at hyperscaler-grade requires more than standing up clusters. It forces a rethink of how the stack is assembled and managed under real demand. Bare metal, virtualized environments, Kubernetes, Slurm, networking, tenant isolation, and security all have to work together in systems that don’t stay stable for long. Provisioning has to be fast. Workloads have to be isolated. GPUs have to be scheduled efficiently across environments that are constantly changing.

That complexity shows up directly in economics.

Data centers are no longer just housing compute. They are producing output, measured in tokens, and the cost per token is becoming the constraint that shapes the market. GPU pricing volatility, supply shortages, and infrastructure inefficiencies all flow upward into API pricing and business viability. Small inefficiencies at the infrastructure layer compound quickly when workloads run continuously and scale across thousands of GPUs.

This is where neoclouds either gain an edge or fall behind. The advantage isn’t just having access to hardware. It’s the ability to operate that hardware efficiently enough to keep costs under control while demand keeps rising.

Scaling adds another layer of pressure. As workloads move from experimentation into continuous operation, clusters need to expand quickly without breaking. That expansion depends on factors that sit outside the traditional cloud conversation, power availability, cooling capacity, physical footprint, and supply chain timing. Bringing more GPUs online is only part of the equation. Powering them, cooling them, and deploying them fast enough becomes the real challenge.

Operators are being pushed into decisions that tie hardware and software together more tightly than before. Liquid cooling, high-density rack design, and co-design between infrastructure and workloads are no longer edge considerations. They are part of the core system that determines how much capacity can actually be delivered.

All of this points to the same conclusion. Neoclouds matter because they are operating inside the tightest part of the system, where access, cost, and scale converge. The market is not waiting for perfect conditions. It is rewarding the teams that can bring capacity online, keep it running efficiently, and expand it under constraint.

That is where the next layer of competition is forming.

If you want to hear how the teams actually doing this are thinking about it, from hyperscaler-grade buildouts to token economics to scaling under real constraints, those conversations are happening next Friday at AI INFRA SUMMIT 5 on May 1st.

• If you’re deploying, financing, or scaling AI infra, this is the place

• If you’re not here, you’re downstream of the people who are

• Most tickets are already snatched up, room is limited

TELUS Health is a global health and wellbeing technology provider delivering digital infrastructure across physical, mental, and financial health systems.

What they deliver

• Electronic medical records and digital health platforms

• Virtual care and remote patient monitoring

• Mental health and employee wellbeing solutions

• AI-driven clinical workflow tools

• Health data infrastructure across providers, insurers, and employers

Why it matters
Healthcare is becoming a data and infrastructure problem. Administrative load, fragmented systems, and rising demand are pushing care delivery to its limits. TELUS Health is embedding AI into clinical workflows to reduce manual work, improve decision-making, and scale care without adding headcount.

Who they serve
Healthcare providers, employers, insurers, and public sector systems operating at scale.

We are looking forward to having their Chief Mental Health Officer, Matthew Chow, join us to speak on how infrastructure decisions impact clinical outcomes, clinician workload, and system capacity. This is one of the few conversations that ties AI infrastructure directly to real-world care delivery, and it brings a needed operator perspective into the room.

Explore TELUS Health to see how they are building infrastructure for modern healthcare systems.

Bay Area Startups Collectively Secured $15.75B This Week

The week started with a $5B investment for Anthropic by Amazon and closed with Google investing $10B more. That $15B made up the bulk of investments this week, more than half of the remaining deals were for less than $10M each.

Exits, IPOs: The Cerebras IPO will likely be the first IPO of 2026 among the short list of AI companies lining up to go public. Cerebras, one of just a few Nvidia competitors, filed their paperwork on Friday. Their $1.1B Series G in February came with an $8.1B valuation and their filing coincided with OpenAI announcing an expansion of their agreement with Cerebras, doubling their purchase of Cerebras hardware/compute to $20B over the next three years. They also loaned Cerebras $1B and received a warrant for Cerebras stock.

Webinar Alert & Date Change: The Fundraising with LinkSV series is this Wednesday, April 29. We'll cover fundraising preparation and introduce a new tool for finding investors, customers and networking. Two attendees will receive 90-day Entrepreneur memberships, plus individual sessions on finding prospective angel investors with LinkSV. Interested? Register here for the link.

Early Stage:

• NeoCognition closed a $40M Seed, the AI agent lab for specialized intelligence

• Humble Robotics closed a $24M Seed, makes fully autonomous, electric haulers designed for cost-effective commercial freight transportation

• C-Infinity closed a $16M Seed, building foundational AI for mechanical design and manufacturing.

• Creao AI closed a $10M Series A, the Super Agent - a persistent, action-taking AI that can get all your digital work done.

• Sleuth Insights closed a $8M Seed, helps strategic biopharma teams turn complex questions into clear answers - in hours.

Growth Stage:

• Reliable Robotics closed a $160M Series C, provides advanced aircraft automation service intended to make aircraft safer and more affordable.

• Omni Analytics closed a $120M Series C, the AI analytics platform that turns company data into a trusted source of truth for AI.

• Orkes closed a $60M Series B, the fastest way to scale distributed systems across microservices, APIs, AI models, and event-driven architectures for any language or framework.

• Afresh Technologies closed a $34M Series C, our A.I.-powered solution optimizes ordering, forecasting, and operations for fresh food departments in brick-and-mortar grocers.

• Anthropic closed a $10B Series G, an AI safety and research company developing AI systems that are helpful, honest and harmless.

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Logan Lemery
Head of Content // Team Ignite

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