AI outpaces today’s infrastructure.
Hyperspeed compute closes the gap: distributed, modular GPU access without long buildouts or procurement drag.
We're QumulusAI, and we're breaking AI’s biggest barriers.
#AI#Hyperspeed#GPU#Infrastructure
🔴 Live NOW — watch here: https://t.co/D5z9UseqBp
Our CEO Mike Maniscalco is on stage with @Cisco + @Cirrascale at #CiscoLive on AgenticOps and end-to-end AI networking, from silos to scale.
▶️ Watch live today! Starts in one hour. Our CEO Mike Maniscalco joins @Cisco + @Cirrascale at #CiscoLive: "AgenticOps and End-to-End AI Networking: From Silos to Scale."
https://t.co/D5z9UsdSLR
10:30 AM PT / 1:30 PM ET
Training frontier models needs 100,000 GPUs in one place. Agentic workloads don't.
So we're building distributed dense compute where demand actually lives.
Catch our CTO at @Cisco Live!
We're at #CiscoLive with opinions on AI infrastructure.
Catch our CEO, Mike Maniscalco, on Center Stage (Bayside B, 10:30 AM Wed): "AgenticOps and End-to-End AI Networking."
Ryan DiRocco, Jim Marino, and Stephen Hunton are on the ground too.
Find us on LinkedIn. Easy to find, hard to out-engineer.
Inference platforms aren't waiting on models. They're waiting on capacity.
680 NVIDIA H200 GPUs. Two clusters. A 2-year contract with two of the fastest-scaling inference platforms in production.
Built with @shadeformai.
Read the press release > https://t.co/4EhjS2lNNK
AI plans move fast.
GPU capacity usually doesn’t.
Stephen Hunton and Mike Halles will be at @Dell Technologies World for QumulusAI. If your team needs capacity for training, inference, fine-tuning, or private AI infrastructure, connect with them on LinkedIn to meet onsite.
Tech Square is one of the densest AI ecosystems in the country. As of June 1, QumulusAI is headquartered in the middle of it.
New corporate HQ inside The Biltmore Innovation Center at @GeorgiaTech.
Proximity isn't a perk. It's the strategy.
> Read More: https://t.co/aievxtvn1S
The GPU problem isn't supply. It's capital.
QumulusAI just closed $26M in lease financing for a 50-node NVIDIA B200 cluster with TFC (subsidiary of Kingsbridge Holdings).
Built to scale. Built to repeat.
> Read more: https://t.co/C5IzuWUuHv
Our clients are working across different hardware, network stacks, and deployment requirements. We believe that means the ability to test, prototype, and validate in realistic environments is an essential advantage.
In this conversation with Lukas Gentele from @vcluster, Ryan DiRocco talks about building an infrastructure lab environment that makes that kind of work easier.
As the stack keeps changing, real-world validation becomes part of the value.
> Watch the full conversation: https://t.co/7WeNQEvY48
AI infrastructure is hard to evaluate when most of the critical pieces are invisible.
That’s part of what makes the @DDNintelligence AI Factory on Wheels interesting.
At NVIDIA GTC 2026, Mike Maniscalco, CEO of QumulusAI, joined James Coomer, SVP Product at DDN, for a conversation inside the nationally touring DDN AI Factory on Wheels.
The exhibit brings AI infrastructure to life through real-world use cases, digital simulations, blueprints, containers, NVIDIA microservices, and deployment models.
For enterprise leaders, that matters.
Because getting from “we need AI” to “we have a working AI factory” requires more than access to GPUs. It requires a clearer understanding of how compute, storage, software, pipelines, and deployment strategy come together.
QumulusAI is featured alongside DDN and other technology providers in the AI Factory on Wheels ecosystem as enterprises look for faster, more flexible paths to production AI.
Watch the full conversation on YouTube: https://t.co/c72qGwyG6n
Contact QumulusAI sales: https://t.co/uIbdMS8qWD
"This new $45 million facility is less about the total dollar amount and more about the velocity of capital. In an industry where procurement delays can stretch into several quarters, the ability to lock in hardware and power capacity ahead of the curve is a vital tactical advantage." — @StevenDickens3 | CEO @HyperFRAME_Res
> Read the full analyst article: https://t.co/XvJn4G30MO
AI roadmaps don’t fail because of ambition. They fail because compute shows up late.
QumulusAI secured a $45M convertible note facility from ATW Partners, with $15M funded to date, to accelerate GPU procurement and infrastructure deployment.
For enterprise AI teams, speed to live cluster matters. That’s the story.
> Read more: https://t.co/RkNO1ZXyDK
Serious AI teams are still being forced to make business decisions through infrastructure constraints they did not choose.
That is part of what makes speed so consequential in this market.
In this conversation with vCluster, we talk about why infrastructure speed is no longer just an operational advantage. It shapes how quickly teams can deploy, test, train, fine-tune, and move into production.
When customers expect a cloud-like experience, but the underlying hardware market is constrained and supply chains are tight, providers have to do more than simply offer access. They have to reduce burden and help customers move.
That is the focus of this discussion.
> Watch here: https://t.co/7WeNQEvY48
#AIInfrastructure #Kubernetes #CloudInfrastructure #MLOps #GPUCloud
🖐 Top five signs your AI development roadmap is failing:
☝️ — Projects delayed or quietly shelved because GPUs weren't available
✌️ — Budget surprises buried in hyperscale invoices
👌 — Engineers context-switching off AI work while they wait for capacity
👊 — A stalled internal debate about whether to stay on a hyperscaler or look elsewhere
🖐 — Leadership asking for faster AI time-to-value without funding the infrastructure to deliver it
If more than one of those is familiar, the new HyperFRAME Research brief is worth thirty minutes.
It introduces the FACTS framework — Flexibility, Access, Cost, Trust, Speed — as a diagnostic for figuring out where the drag is actually coming from.
🤫 Hint: It's your infrastructure.
> Download it today.
https://t.co/mxfCiIWpK1
"As fast as the market is moving from Hopper, to Blackwell, to Rubin... the customer's ability to test and understand performance profiles — or even compatibility across platforms — is critical. And the last thing they want to do is contract for something, wait for it, get it late and realize they're not ready to run on it." — Ryan DiRocco (CTO, @QumulusAI)
Ryan joined @vcluster's Lukas Gentele (CEO and Co-Founder) for a conversation about hyperspeed GPU deployment, partnership activation, and client provisioning.
It's a 30-minute chat that lays the groundwork for how vCluster and QumulusAI are working together to provide the next generation of AI compute for the industry's fastest innovators.
> Watch it now. https://t.co/ylGVt3jUAv
Where's AI heading next and will the nation's infrastructure be able to support it?
Join QumulusAI CEO, Mike Maniscalco, and other industry leaders for Centri's 2026 Capital Conference at Nasdaq on Tuesday, April 14, to discuss "AI at Scale: Capital, Compute, and the Infrastructure Powering the Next Phase of Growth."
For the full conference agenda, please visit: https://t.co/ZNMX6px4rT
#Nasdaq
#Conference
#CentriCapitalConference
#CapitalMarkets
#ArtifificialIntelligence
#AI
Most GPU infrastructure conversations get stuck on specs instead of talking about the FACTS:
→ Flexibility → Access → Cost → Trust → Speed
Does your AI infrastructure provider prioritize the FACTS?
#AIInfrastructure#GPU#AI