Cyfuture delivers advanced technology solutions that empower enterprises to build and scale digital capabilities. The company provides cloud computing, data center, and AI infrastructure services designed for performance, reliability, and scalability. Among its flagship offerings, Cyfuture operates a robust AI GPU-as-a-Service (GPUaaS) platform. This platform provides enterprises with on-demand access to high-performance GPUs through a flexible and scalable cloud environment.
As a result, organizations can train, test, and deploy AI, machine learning, and deep-learning models without making substantial capital investments in expensive hardware. Furthermore, Cyfuture’s GPU cloud integrates cutting-edge processors, including NVIDIA H100 and L40s, ensuring the computational power required for complex AI workloads. At the same time, the platform allows users to scale seamlessly, from a single GPU to large multi-GPU clusters, while following a transparent pay-as-you-use pricing structure.
In addition, Cyfuture strengthens the ecosystem with pre-configured AI frameworks, high-availability architecture, and enterprise-grade security controls. Consequently, businesses can accelerate AI development cycles, streamline deployment, and optimize both cost and performance with greater operational efficiency.
In an exclusive interaction with The Interview World during the India AI Impact Expo 2026, Syed Mohammed Idresh, Account Manager at Cyfuture, shares detailed insights into the company’s GPU-as-a-Service platform. He explains how the GPU service operates in practice. Moreover, he outlines the pricing structure and compares it with global GPU service providers. He also discusses market reception, highlights the number of clients already onboarded, and presents Cyfuture’s strategic roadmap for expansion. The following section captures the key insights from this engaging and informative conversation.
Q: Could you elaborate on the GPU-as-a-Service offering provided by Cyfuture for AI developers, particularly how it supports model inference and AI workloads?
A: Cyfuture offers a comprehensive portfolio of advanced GPUs to support diverse AI and high-performance computing workloads. The company deploys a wide range of processors, including L40S, A100, H100, H200, B100, Gaudi 2, T4, and AMD MI300X. Each GPU addresses specific computational requirements, thereby enabling organizations to select the architecture best suited to their AI models and data workloads.
At present, however, market demand increasingly favours the B100 GPU. Clients actively request this processor because it delivers strong performance at a highly competitive price point. As a result, organizations can access powerful computing capabilities while maintaining greater cost efficiency.
By contrast, GPUs such as A100 and H200 often command significantly higher pricing. Consequently, many enterprises consider alternatives like B100 and L40S, which serve as practical and cost-effective options for a broad range of AI applications. These GPUs frequently act as the foundational infrastructure for many client deployments.
Nevertheless, many organizations initially struggle to determine which GPU configuration best fits their workload. Recognizing this challenge, Cyfuture provides dedicated evaluation and testing services. Through this approach, clients can run pilot workloads and test their applications on different GPU architectures. They can then assess performance, scalability, and cost implications before making a final selection. Ultimately, this process enables enterprises to identify the most suitable GPU environment with confidence and precision.
Q: Could you explain the process through which you provide GPU services to your clients?
A: Cyfuture actively procures advanced GPUs to strengthen its AI infrastructure capabilities. Because the company operates its own data centers and maintains a large fleet of servers, it can integrate these GPUs directly into its existing infrastructure. Consequently, Cyfuture deploys GPUs across its facilities in much the same way it provisions traditional server resources.
Building on this foundation, the company delivers GPU-as-a-Service (GPUaaS) through its cloud platform. Clients can therefore access high-performance GPUs on demand without investing in dedicated hardware. In practice, the service operates just like other cloud and data center offerings. Users request the required resources, the platform provisions them instantly, and organizations scale usage according to workload requirements.
As a result, Cyfuture enables enterprises to access powerful GPU computing through a simple, flexible, and cloud-based service model.
Q: How does your pricing model compare with other global GPU service providers?
A: Cyfuture delivers its GPU cloud services at a significantly lower cost than major global hyperscalers. In comparison with platforms such as Amazon Web Services and Microsoft Azure, we offer pricing that is approximately 30–40 percent more cost-efficient.
This advantage stems from Cyfuture’s fully owned and operated infrastructure. The company runs its own data centers, maintains its own hardware resources, and manages the entire service stack internally. Consequently, it avoids the additional markups or intermediary service charges that often increase costs on other platforms.
As a result, Cyfuture can deliver competitive GPU computing services while maintaining lower operational costs. This integrated infrastructure model ultimately enables the company to pass substantial savings directly to its clients.
Q: How has the market responded to your GPU-as-a-Service offering, and how many clients have you onboarded so far?
A: Cyfuture continues to receive a strong and encouraging response from the market. As demand for AI infrastructure accelerates, the company’s GPU cloud services have gained significant traction among enterprises. Consequently, Cyfuture now finds itself in high demand across multiple industry segments.
Moreover, the company has actively participated in the India AI Impact Expo 2026, further strengthening its visibility within the national AI ecosystem. This engagement has allowed Cyfuture to showcase its infrastructure capabilities and connect directly with technology leaders and enterprise decision-makers.
As a result of this growing momentum, the company has already onboarded approximately 150 enterprise clients. This expanding client base reflects both the market’s confidence in Cyfuture’s GPU-as-a-Service platform and the increasing need for scalable AI computing infrastructure.
Q: What are your key strategic plans for the next five years?
A: Over the next five years, Cyfuture intends to pursue strong and sustained growth. The company plans to expand its market presence steadily while attracting a larger base of enterprise clients. At the same time, it aims to strengthen its GPU infrastructure capabilities and deepen its footprint in the AI cloud ecosystem. More importantly, Cyfuture has set a clear regional objective. It seeks to emerge as the leading provider of GPU infrastructure services in the Noida region. To achieve this goal, the company will continue investing in advanced GPU technologies, expanding its data center capacity, and delivering cost-efficient, high-performance AI computing services to enterprises.
