Tata Communications builds India’s first national AI network with AWS

Tata Communications, one of India’s largest telecommunications providers, has partnered with Amazon Web Services (AWS) to build a specialized national network designed specifically for artificial intelligence workloads. This infrastructure represents one of the most significant AI-focused network deployments in India to date, connecting AWS’s major data centers across three key cities with high-speed, low-latency connections optimized for machine learning and AI applications.

The collaboration addresses a critical infrastructure gap as Indian businesses increasingly adopt AI technologies. Unlike traditional networks designed primarily for web browsing and basic data transfer, AI workloads require massive bandwidth and minimal delays to handle the enormous data flows involved in training machine learning models and running real-time AI applications.

The infrastructure backbone

The new network will connect AWS infrastructure across Mumbai, Hyderabad, and Chennai through a purpose-built national long-haul network. AWS operates full data center regions in Mumbai and Hyderabad—these are clusters of data centers that provide complete cloud computing services including storage, processing power, and networking. In Chennai, AWS maintains what’s called “Direct Connect” infrastructure, which provides dedicated network connections between customer facilities and AWS services, along with edge network infrastructure that brings cloud services closer to end users.

This three-city connection creates a triangle of high-performance infrastructure spanning some of India’s most economically important regions. Mumbai serves as the country’s financial capital, Hyderabad has emerged as a major technology hub, and Chennai anchors the southern industrial corridor.

The scale of this deployment sets it apart from typical network projects. According to Tata Communications, this represents their largest National Long-Distance program to date in terms of both physical scale and data-carrying capacity. The network is engineered to handle what the industry calls “data-intensive workloads”—applications that move and process enormous amounts of information simultaneously.

Why AI needs specialized networks

Artificial intelligence applications place unique demands on network infrastructure that traditional internet connections struggle to meet. When companies train AI models, they’re essentially feeding massive datasets through complex mathematical processes that can take days or weeks to complete. Any network delays or interruptions can significantly slow this process or even corrupt the training data.

Generative AI applications, like those that create text, images, or code, require real-time responsiveness. Users expect immediate results when they ask an AI system to write content or analyze data. This demands what network engineers call “low-latency” connections—pathways that minimize the time it takes for data to travel between points.

High-performance computing (HPC) applications, which use multiple computers working together to solve complex problems, need networks that can coordinate seamlessly between different processing units. Financial modeling, weather prediction, and drug discovery all rely on HPC systems that require specialized network infrastructure.

Business applications across sectors

The new network infrastructure is designed to enable businesses across multiple industries to deploy AI applications at scale. In healthcare, hospitals and research institutions could use the network to run AI-powered diagnostic tools that analyze medical images or predict patient outcomes. These applications require processing large amounts of sensitive data quickly while maintaining strict security and privacy standards.

Financial services companies could leverage the infrastructure for real-time fraud detection, algorithmic trading, and risk assessment. Banks and investment firms increasingly rely on AI systems that must analyze market data and make decisions within milliseconds—capabilities that demand ultra-fast network connections.

Educational institutions could use the network to deploy AI-powered learning platforms, research tools, and administrative systems. As India’s education sector undergoes digital transformation, universities and schools need infrastructure capable of supporting AI applications for personalized learning and academic research.

Manufacturing companies could connect factory systems to AI-powered optimization tools that improve production efficiency and predict equipment maintenance needs. These industrial AI applications often require processing data from hundreds of sensors and machines simultaneously.

Security and compliance framework

The network incorporates what both companies describe as “robust security controls” designed to meet India’s regulatory requirements for data protection. This includes compliance with the country’s data localization requirements, which mandate that certain types of sensitive data must be stored and processed within Indian borders.

AWS brings its enterprise-grade security technologies to the partnership, including encryption systems that protect data as it moves across the network and access controls that ensure only authorized users can reach specific resources. For businesses handling sensitive information, these security measures are essential for regulatory compliance and customer trust.

The infrastructure also includes redundancy systems designed to maintain service availability even if individual network components fail. This high-availability design is crucial for businesses that depend on AI applications for critical operations.

Market implications

This partnership reflects the growing importance of India’s digital economy and the country’s emergence as a global hub for AI development and deployment. India’s technology sector has been rapidly adopting AI across industries, from software development to customer service to financial analysis.

“AI is transforming industries globally, and our collaboration with AWS positions us at the forefront of this revolution in India,” said Genius Wong, executive vice president and chief technology officer at Tata Communications. “Together, we’re enabling a network that not only meets current demands but anticipates the needs of tomorrow.”

Jesse Dougherty, vice president for network edge services at AWS, emphasized the infrastructure’s role in supporting India’s expanding digital economy: “This collaboration with Tata Communications will further enable our customers in India to innovate at scale with cloud and generative AI, and drive growth in India’s rapidly expanding digital economy.”

The timing aligns with AWS’s broader expansion in India. The company launched its Hyderabad cloud region in November 2022, which includes three availability zones—separate data center facilities within a region that provide redundancy and disaster recovery capabilities. AWS has indicated plans for further expansion in Hyderabad’s data center market, signaling long-term commitment to the Indian market.

Looking ahead

The network infrastructure is designed with future growth in mind, anticipating that AI workloads will continue to increase in both volume and complexity. As more Indian businesses adopt AI technologies and as AI models become more sophisticated, the demand for specialized network infrastructure will likely grow significantly.

This partnership also positions both companies to compete more effectively with other cloud providers and telecommunications companies seeking to capture India’s growing AI market. By combining Tata Communications’ extensive domestic network infrastructure with AWS’s cloud computing expertise, the collaboration creates a differentiated offering for enterprise customers.

The project represents a broader trend toward purpose-built infrastructure for emerging technologies. As AI applications become more central to business operations, companies are investing in specialized infrastructure rather than trying to adapt existing systems for new use cases.