QumulusAI

QumulusAI Provides A Clear Roadmap for Scaling AI Platforms to Thousands of Users

Scaling AI

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…

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Latest

Client Stories - QumulusAI
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…

Read More
Client Stories - QumulusAI
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…

Read More
Client Stories - QumulusAI
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…

Read More
Client Stories - QumulusAI
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…

Read More
Client Stories - QumulusAI
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…

Read More
Client Stories - QumulusAI
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…

Read More

Latest

promoted
How to Succeed After Getting Promoted: Seeking Feedback, Acting with Intention, and Leading with Perspective
April 16, 2026

Stepping into a leadership role today isn’t just a step up—it’s a shift into constant visibility, where expectations arrive immediately and the margin for error narrows. As organizations flatten structures and demand faster decisions, newly promoted leaders are expected to deliver impact from the outset, often without the space to fully adjust. According to…

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AI in business
A Practical Conversation About AI in Business: From Hype to Real-World Impact
April 15, 2026

Artificial intelligence has moved from buzzword to boardroom priority at a staggering pace. Yet despite widespread adoption, many organizations are still struggling to turn experimentation into measurable business value—some estimates suggest the majority of enterprise AI initiatives fail to scale successfully. As AI becomes “table stakes” across industries, the real challenge is no longer…

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weekly drive-in
Metropolis: Weekly Drive-in
April 15, 2026

Metropolis “Weekly Drive In” reflects a new era of storytelling where AI meets real-world execution, turning everyday field performance into momentum. Centered on genuine conversions and local wins, the series highlights how the company is scaling not just through technology, but through visibility and shared recognition. In an emerging recognition economy, these updates act…

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Drive In, Drive Out: The Rhythm of Metropolis
April 15, 2026

Behind the seemingly mundane choreography of a drive-in lies a broader story about how modern cities script behavior, turning even the simplest actions into rehearsed routines. What looks like repetition is really a quiet testament to systems designed for flow and control, where efficiency often outweighs individuality. In places like Metropolis, the rhythm of…

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Latest Client Stories - QumulusAI

Scaling AI
Client Stories - QumulusAI
QumulusAI Provides A Clear Roadmap for Scaling AI Platforms to Thousands of Users
February 18, 2026

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…

Read More
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…

Read More
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…

Read More
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…

Read More
business insights
Client Stories - QumulusAI
Amberd Delivers Real-Time Business Insights, Cutting Executive Reporting From Weeks to Minutes With ADA
February 18, 2026

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…

Read More
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…

Read More
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…

Read More
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…

Read More
private LLM
Client Stories - QumulusAI
QumulusAI Secures Priority GPU Infrastructure Amid AWS Capacity Constraints on Private LLM Development
February 18, 2026

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…

Read More

Latest Industry IQ - QumulusAI

custom AI chips
Industry IQ - QumulusAI
Custom AI Chips Signal Segmentation for AI Teams, While NVIDIA Sets the Performance Ceiling for Cutting-Edge AI
February 18, 2026

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…

Read More
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’…

Read More
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…

Read More
Other QumulusAI Articles
Amberd Moves to the Front of the Line With QumulusAI’s GPU Infrastructure
February 18, 2026

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…

Read More
QumulusAI Secures Priority GPU Infrastructure Amid AWS Capacity Constraints on Private LLM Development
February 18, 2026

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…

Read More
Custom AI Chips Signal Segmentation for AI Teams, While NVIDIA Sets the Performance Ceiling for Cutting-Edge AI
February 18, 2026

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…

Read More
OpenAI–Cerebras Deal Signals Selective Inference Optimization, Not Replacement of GPUs
February 18, 2026

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’…

Read More
NVIDIA Rubin Brings 5x Inference Gains for Video and Large Context AI, Not Everyday Workloads
February 18, 2026

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…

Read More