QumulusAI - Breaking AI’s Biggest Barriers
QumulusAI is a fully integrated AI infrastructure solution, encompassing the entire stack—from high-performance computing clouds to both on- and off-grid data centers powered by natural gas generation. Our scalable, energy-efficient solutions eliminate computational bottlenecks in AI development, ensuring enterprises and innovators have the compute resources they need, when they need them. With QumulusAI, development teams train models faster, deploy smarter, and push the limits of AI innovation.
Industry IQ
Custom AI Chips Signal Segmentation for AI Teams, While NVIDIA Sets the Performance Ceiling for Cutting-Edge AI
Microsoft’s introduction of the Maia 200 adds to a growing list of hyperscaler-developed processors, alongside offerings from AWS and Google. These custom AI chips are largely designed to improve inference efficiency and optimize internal cost structures, though some platforms also support large-scale training. Google’s offering is currently the most mature, with a longer production…
OpenAI–Cerebras Deal Signals Selective Inference Optimization, Not Replacement of GPUs
OpenAI’s partnership with Cerebras has raised questions about the future of GPUs in inference workloads. Cerebras uses a wafer-scale architecture that places an entire cluster onto a single silicon chip. This design reduces communication overhead and is built to improve latency and throughput for large-scale inference. QumulusAI Senior Product Manager Mark Jackson says Cerebras’…
NVIDIA Rubin Brings 5x Inference Gains for Video and Large Context AI, Not Everyday Workloads
NVIDIA’s Rubin GPUs are expected to deliver a substantial increase in inference performance in 2026. The company claims up to 5 times the performance of B200s and B300s systems. These gains signal a major step forward in raw inference capability. Mark Jackson, Senior Product Manager at QumulusAI, explains that this level of performance is…
Client Stories
QumulusAI Provides A Clear Roadmap for Scaling AI Platforms to Thousands of Users
Scaling AI platforms can raise questions about how to expand across locations and support higher user volumes. Growth often requires deployments in multiple data centers and regions. Mazda Marvasti, the CEO of Amberd, says having a clear path to scale is what excites him most about the company’s current direction. He notes that expanding…
Complex AI Software Should Be Delivered as a Managed Service
Artificial intelligence software is increasing in complexity. Delivery models typically include traditional licensing or a managed service approach. The structure used to deploy these systems can influence how they operate in production environments. The CEO of Amberd, Mazda Marvasti, believes platforms at this level should be delivered as a managed service rather than under…
Facing High GPU Costs and Infrastructure Constraints, Amberd Turned to QumulusAI for Fixed-Cost AI
Providing managed AI services at a predictable, fixed cost can be challenging when hyperscaler pricing models require substantial upfront GPU commitments. Large upfront commitments and limited infrastructure flexibility may prevent providers from aligning costs with their delivery model. Amberd CEO Mazda Marvasti encountered this issue when exploring GPU capacity through Amazon. The minimum requirement…
AI Enables Faster Business Decisions, Giving Startups an Edge Over Traditional Companies
Speed in business decisions is becoming a defining competitive factor. Artificial intelligence tools now allow smaller teams to analyze information and act faster than traditional organizations. Established companies face increasing pressure as decision cycles shorten across industries. Mazda Marvasti, CEO of Amberd, says new entrants are already using AI to accelerate business decisions. He…
Amberd Delivers Real-Time Business Insights, Cutting Executive Reporting From Weeks to Minutes With ADA
Many organizations struggle to deliver real-time business insights to executives. Traditional workflows require analysts and database teams to extract, prepare, and validate data before it reaches decision makers. That process can stretch across departments and delay critical answers. The CEO of Amberd, Mazda Marvasti, states that the cycle to answer a single business question…
No Idle GPUs, No Data Leakage: QumulusAI Maximizes GPU Utilization for Multiple Customers on Shared Infrastructure
Multi-tenant GPU infrastructure is becoming essential as AI deployments scale across customers. Organizations must maximize GPU utilization while maintaining strict data isolation. Idle compute reduces efficiency, yet shared environments can introduce security risks if not designed properly. Optimizing GPU cycles across multiple customers is essential to maintaining performance and cost efficiency. Mazda Marvasti, the…
QumulusAI Brings Fixed Monthly Pricing to Unpredictable AI Costs in Private LLM Deployment
Unpredictable AI costs have become a growing concern for organizations running private LLM platforms. Usage-based pricing models can drive significant swings in monthly expenses as adoption increases. Budgeting becomes difficult when infrastructure spending rises with every new user interaction. Mazda Marvasti, CEO of Amberd, says pricing volatility created challenges as his team expanded its…
Amberd Moves to the Front of the Line With QumulusAI’s GPU Infrastructure
Reliable GPU infrastructure determines how quickly AI companies can execute. Teams developing private LLM platforms depend on consistent high-performance compute. Shared cloud environments often create delays when demand exceeds available capacity. Amberd CEO Mazda Marvasti says waiting for GPU capacity did not align with his company’s pace. Amberd required guaranteed availability to support its…
QumulusAI Secures Priority GPU Infrastructure Amid AWS Capacity Constraints on Private LLM Development
Developing a private large language model (LLM) on AWS can expose infrastructure constraints, particularly around GPU access. For smaller companies, securing consistent access to high-performance computing often proves difficult when competing with larger cloud customers. Mazda Marvasti, CEO of Amberd, encountered these challenges while scaling his company’s AI platform. Because Amberd operates its own…