As enterprise AI moves from experimentation to large-scale deployment, India’s cloud ecosystem is undergoing a structural shift—from global hyperscaler dependence to locally built, sovereign infrastructure. In this conversation with CIO&Leader, Manoj Dhanda, Founder & CEO of Utho Cloud, outlines how this transition is being driven by the need for cost predictability, data sovereignty, and low-latency performance. He argues that cloud is no longer just a consumption model, but a strategic capability layer shaping business outcomes. From tackling the rising “cloud burn” challenge for startups to enabling national AI ambitions through India-hosted infrastructure, Dhanda presents a compelling case for rethinking cloud strategy—one that balances scalability with control, and innovation with financial discipline in an AI-first enterprise landscape.
Founder & CEO
Utho Cloud
CIO&Leader: How is India’s cloud infrastructure evolving to support enterprise AI at scale, independent of hyperscaler dependency?
Manoj Dhanda: India’s cloud infrastructure is transitioning from consumption-based to capability-based. Companies used to rely on global hyperscalers to achieve the scalability they needed. Still, now they are building local infrastructure to deliver high-performance AI capabilities while complying with regulations and controlling expenses. The growth of enterprise AI has made low-latency processing, data residency and predictable cost requirements essential for businesses to succeed.
Additionally, Indian cloud service providers are allocating resources to develop data centers that support GPU processing and high-density computing, as well as multiple regional data facilities built for artificial intelligence and machine learning operations. This evolution allows enterprises to process training and inference tasks at locations near their data sources, resulting in faster performance and better operational results.
The demand for sovereign cloud environments has been growing as these systems enable organizations to meet legal requirements and industry-specific compliance standards. The current market trend is decreasing enterprise reliance on hyperscalers, providing organizations with greater independence and control over their business plans. India is rapidly adopting a hybrid multi-cloud system that relies on domestic service providers to establish secure AI deployment methods.
CIO&Leader: What architectural choices enable Utho Cloud to deliver up to 60% cost savings without compromising performance?
Manoj Dhanda: At Utho Cloud, we developed our platform to achieve cost optimization through its fundamental design elements. The infrastructure design of our system uses a lean, modular approach, focusing on eliminating unnecessary components that are common in hyperscale environments. By focusing on efficient resource allocation and avoiding overprovisioning, we ensure customers pay only for what they use.
Our organization has created an optimized computing platform that delivers maximum performance at the lowest possible cost. The system uses current processors combined with effective virtualization and special configurations that meet particular requirements for artificial intelligence and advanced computing operations. Additionally, our focus has been on building strong core infrastructure for compute, networking, storage, and databases, rather than adding unnecessary microservices that users may not need. While hyperscaler costs tend to rise significantly with scale, platforms like Utho deliver similar capabilities through a more cost-efficient infrastructure approach.
The essential aspect of our operations depends on choosing the right local market to establish our business. The Indian data centers enable us to reduce data transmission costs while minimizing delays, leading to substantial reductions in overall cloud computing costs. The organization uses clear pricing structures to eliminate hidden fees common on big platforms.
The architectural choices we made enable us to deliver enterprise-level performance while achieving 60% cost reductions, resulting in affordable cloud services for businesses of all sizes.
CIO&Leader: Why are cloud costs emerging as a “burn problem” for startups, and how should founders rethink infrastructure strategy?
Manoj Dhanda: Cloud costs have become a major concern for startups because what initially appears as a flexible, pay-as-you-go model often scales unpredictably with growth. As startups expand their user base and workloads, costs for compute resources, storage, and especially data transfer services rise rapidly. Many founders realize too late that their infrastructure decisions are directly impacting their runway.
The “burn problem” occurs when organizations lack both visibility and control. Startups often over-provision resources to ensure performance, or they rely on default configurations that are not cost-efficient. The combination of complex pricing models and concealed fees creates difficulties for users who want to estimate their costs with precision.
Cloud strategy requires founders to treat it as a fundamental business choice rather than a technical detail. Organizations should select a platform with clear pricing information as they establish their regular workload processes and develop systems that strike a balance between system performance and operational efficiency. Exploring different cloud providers that focus on maintaining cost stability through local infrastructure solutions will create important advantages. Sustainable growth requires businesses to select their infrastructure solutions according to their financial needs, ensuring that cloud spend scales proportionately with business value, not just usage.
CIO&Leader: How critical is data sovereignty in shaping cloud adoption decisions for Indian enterprises today?
Manoj Dhanda: Data sovereignty has become a central factor in cloud adoption decisions for Indian enterprises that operate in regulated industries, including finance, healthcare, and government. As organizations become more aware of data privacy and security issues, they are choosing solutions that keep their data within national boundaries and under local government control.
The shift toward this trend is getting stronger because of regulatory frameworks and new data protection regulations. Enterprises now need better control over their data storage locations and processing methods. The demand for cloud providers that operate data centers in India and follow local regulations has increased among businesses.
Data sovereignty enables organizations to build customer trust beyond basic compliance requirements. Businesses show more willingness to use cloud services when they understand that their protected data will remain safe from international legal obligations and foreign threats. The system reduces latency while improving performance for users accessing applications within the country.
CIO&Leader: What role will India-hosted infrastructure play in scaling public digital platforms and national AI initiatives?
Manoj Dhanda: India-hosted infrastructure will be foundational in scaling the next generation of public digital platforms and national AI initiatives. As the country continues to build large-scale digital ecosystems ranging from governance platforms to AI-driven public services, the need for reliable, secure, and locally controlled infrastructure becomes paramount. The deployment of hosting infrastructure in India enables organizations to meet data localization standards while achieving faster data processing speeds and lower latency times. This is especially important for real-time applications such as digital identity systems, healthcare platforms, and smart city solutions, where responsiveness and reliability are critical.
Local infrastructure delivers the essential computing resources that national AI projects need to develop large models using Indian datasets. The system protects sensitive information by keeping it within national borders, helping maintain privacy rights and national strategic control. India-based cloud platforms deliver cost savings that enable government organizations to implement and maintain extensive public systems. The country can establish resilient digital systems to secure its future technological independence and equal digital expansion by reducing its reliance on foreign services.
CIO&Leader: How are SaaS and AI startups rebalancing priorities between scalability, cost predictability, and control?
Manoj Dhanda: SaaS and AI startups are focusing less on fast growth and more on long-term stability. The importance of scalability matches the current need for businesses to establish predictable costs and maintain control over their operations. Startups have begun to understand that uncontrolled cloud expenditures will reduce their profit margins and create financial obstacles that will threaten their business sustainability.
As a result, they are actively seeking infrastructure solutions that provide clear pricing models and eliminate unexpected costs. This allows them to plan better and align expenses with revenue growth. The present situation requires companies to establish their power to manage their infrastructure systems. Startups require the capability to build custom systems, which will help them manage their workloads while preventing them from getting trapped with particular suppliers. AI companies need this capability, as they depend on performance tuning and data management to succeed. Startups implement hybrid and multi-cloud strategies, enabling them to find the best solution by using multiple providers to meet their various needs. The organization aims to establish a resilient infrastructure system that will enable its expansion while safeguarding its financial resources and business operations.
CIO&Leader: What does a globally competitive, India-origin cloud stack need to look like over the next five years?
Manoj Dhanda: A globally competitive, indigenous cloud stack must be built on three core pillars: performance, sovereignty, and cost efficiency. Over the next five years, it will need to evolve beyond basic infrastructure services to offer a comprehensive ecosystem that supports advanced workloads, particularly in AI and data analytics.
The stack needs to provide high-performance computing capabilities, including GPU systems that enable extensive AI training and inference. The system needs to establish data sovereignty as its primary design principle, which enables it to comply with all relevant data protection laws while maintaining user trust.
The system needs to establish data sovereignty as its primary design principle, which enables it to comply with all relevant data protection laws while maintaining user trust. Indian cloud platforms need to establish connections with international systems while providing customers the ability to switch between different service providers. The system needs to support both open standards and containerization, as well as hybrid cloud architectures. Startups and emerging enterprises will rely on cost competitiveness as their major deciding factor. The company needs to show clear pricing and resource efficiency to build its international presence. The India-based cloud stack needs to deliver both technical superiority and operational freedom to become the top choice for worldwide cloud customers.