Tamanna Sait

As engineers actively working on AI Infra, these are exactly the problems we are living, breathing, thinking and solving each day. The reality is AI Infrastructure needs to make it easier to integrate new suppliers and vendors that can meet the cooling and power needs. Reliable data centers need end-to-end monitoring, correlation, and continuous diagnostics across the critical environment (power, cooling, sensors), compute (cpu, memory, AI compute) and network. Today the critical environment still remains a series of walled gardens. These often use proprietary APIs. Having more open standards and integration will help a lot. Standardized CDUs, manifolds and QDs is a great starting point. More integrations with open source exporters and collectors will also help a lot here.

We are excited to announce our partnership with @netboxlabs to eliminate configuration drift, close the gap between intended design and live operations, and accelerate time-to-first-token for AI factories.

100% agree that all AI factories need sustainable and reliable deployment and need to achieve real financial payback for customers. The hardest part of building an AI Factory isn’t getting AI compute. It’s turning space, power and hardware into capacity that serves its first token in record time, and then keeping that capacity productive every day after. These AI factories need to be enabled in days and not months of debugging to maximize the ROI and meet the net “X” days of financing commitments. Every single day this capacity is not serving tokens, it will impact the financial payback for customers.

Yes, the future is about heterogeneous compute (aka Disaggregated Inference Architecture) which will give us more ways to match workloads to hardware. It will also raise the bar for orchestration, observability, and proactive operations. This infrastructure model and deployment will carry the most operational complexity of anyone in the stack. The winners will not just have the fastest silicon; they will be the ones who can deploy, operate, and support mixed fleets with the reliability enterprises expect.

From my experience, this is factually accurate..any anomalies and leaks with Liquid Cooling can take the entire AI FACTORY down for days!! This is just one of the many triggers and reasons. Today, there is a lack of end-to-end monitoring and unified correlation across critical environment, compute, and network layers, which is absolutely needed to deliver a reliable data center as a service. We need holistic telemetry correlation across environmental, compute, and networking domains to break down monitoring silos and deliver complete operational visibility end to end. In addition to that, we need topology-aware root cause analysis, which enables us to pinpoint root causes precisely and quickly. By combining the physical asset topology with real-time diagnostic signals, we can get to the root cause of the problem to solve it as soon as possible, and pinpoint exactly where it is happening. We cannot build assuming nothing will fail. It is about how resilient and fault tolerant we are. It is about how quickly and proactively we can detect, root cause, mitigate and recover end-to-end.

Congratulations @Compute_Labs Team on the launch of Compute Labs Financing platform! Look forward to our continued partnership and collaboration as we enable more and more AI Factories to manufacture Intelligence with best reliability and availability, operational excellence and maximize the ROI.

This is a Big moment for NEYON AI that we launched 🚀just in time..NEYON AI provides all-in-one software platform and physical execution layer delivering cradle-to-grave AI Factory deployment and operations..."An autonomous proactive EYE ON your AI Factory to maximize goodput"

As we build out these AI Factories at GW scale; procuring space, power and GPUs is just the first step. Maximizing the Return on Investment (ROI) requires continuous optimized software and hardware availability and ensuring we deploy and bring-up the AI Factories in days and not after months of debugging.

🚀 Exciting News: Announcing the Launch of NEYON AI Inc. 🚀 Along with my co-founders, Jungho Ahn (@pobby21) and Brian Wolfe, we are thrilled to announce the official launch of our startup, NEYON AI Inc. (@neyonai26 )! There are moments in life when facing a critical bottleneck transforms from a daily pain point into a calling. We realized that the challenges we were experiencing in the AI infrastructure space weren't unique to us—thousands of enterprises, developers, and operators are hitting the exact same wall. We built NEYON AI to break that wall down. ⚡ The Problem: Space, Power, and GPUs are Only Step One. In the race to scale artificial intelligence, securing hardware is just the baseline. True optimization and maximizing Return on Investment (ROI) requires continuous, highly complex software and hardware orchestration. Without it, precious compute sits idle, overhead spikes, and breakthrough technology stalls. 👁️ The Solution: The Automated, Proactive Eye on Your AI Factory To solve this, we have launched NEYON AI—An asset-light all-in-one fully integrated software platform and physical execution layer delivering cradle-to-grave AI Factory deployment and operations. We act as an autonomous, proactive eye over your infrastructure, eliminating wasted energy and idle cycles to maximize goodput. 🙏 A Heartfelt Thank You To our early investors, pioneering customers, and strategic partners: thank you for your unwavering belief in our team and our technology. We are officially on the grid, and we are just getting started. If you are looking to optimize your AI Factory deployment, scale your infrastructure seamlessly, or join a team that values Velocity with Precision, let’s connect! ➡️ Visit us at [neyon.ai]. Follow us on X: nitter.cf/neyonai26 and LinkedIn[linkedin.com/company/neyon-a…]