Indore (CEN2)

A centrally located, hyperscale-ready AI Factory designed to support scalable,
low-latency AI workloads, enabling both centralised training and distributed
edge inference across enterprise and cloud networks
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About Indore CEN2

Central AI and Edge Compute Hub
for Low-Latency Workloads

Spanning 4 acres in Indore, CEN2 is a purpose-built AI Factory designed to deliver scalable, high-density
AI infrastructure in central India. Serving as both a central compute hub and an edge aggregation point,
it enables enterprises and hyperscalers to deploy latency-sensitive AI workloads, regional inference, and
distributed cloud applications efficiently from a single facility.

Power

Indore is set to deliver 80MW power, scaling from 20MW by 2026 to 80MW with rack densities 150kW+ per rack for intensive AI workloads.

Connectivity

Carrier-neutral, multi-fiber architecture, providing high-throughput connectivity across national networks and distributed edge locations.

Cooling

Direct-to-chip liquid cooling (DCLC) and Rear Door Heat Exchange (RDHx) cooling architecture with N+1 distributed redundant systems, using high-efficiency heat rejection to minimize energy consumption and enable sustainable, low-PUE operations.

Security

7-layer defenses with biometric controls and TIA-942 Rating and SOC II Type II compliance.

Indore AI Factory
at a Glance

Location Benefits

Why Indore AI Factory?

Indore's central location makes it an ideal site for deploying latency-sensitive AI and edge workloads across India. Positioned along key national fiber corridors, the city enables efficient aggregation of data from distributed edge locations while maintaining balanced reach to cloud and enterprise networks nationwide. The region offers mature power and digital infrastructure, low seismic risk, and growing access to technical talent and logistics networks. Combined with a carrier-neutral connectivity model and scalable AI-ready infrastructure, Indore CEN2 provides a cost-effective, resilient foundation for enterprises and hyperscalers building distributed AI architectures.

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