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# Tata Communications to spend $450M on AI fibre network across India

**[The Next Web](https://daily.dev/sources/tnw)** · 2 min read · 0 upvotes · 0 comments

## Summary

Tata Communications will spend close to $450M on about 10,000km of new long-distance fibre linking India's AI data-centre hubs. The work happens in three phases, starting with a corridor connecting Mumbai, Pune, Hyderabad and Chennai, with later phases reaching Vizag, Bhubaneswar, Jamnagar and GIFT City. The build adds about 6 petabits per second of capacity on top of the company's current 1.25 petabits per second network in India, arriving between the 2030 and 2036 financial years. The project is funded from operating cash flow, according to those reports, and will connect to the company's existing 700,000km of undersea and land fibre. It builds on an earlier 18,000km fibre build for Amazon Web Services due to finish by the end of 2026.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenextweb.com/news/tata-communications-450m-ai-fibre-network-india>

## Questions this post answers

### How much is Tata Communications spending on its new AI fibre network in India?

Tata Communications plans to spend close to $450 million (about Rs 4,350 crore) on roughly 10,000km of new long-distance fibre across India. The project connects AI data-center hubs including Mumbai, Pune, Hyderabad, Chennai, Vizag, Bhubaneswar, Jamnagar, and GIFT City, funded from operating cash flow in three phases.

_Track how telecom investment is reshaping AI data-center capacity on daily.dev._

### How much extra network capacity will Tata Communications' new fibre build add in India?

The new fibre build adds about 6 petabits per second of capacity to Tata Communications' India network, which currently carries 1.25 petabits per second. That extra capacity is expected to arrive between the 2030 and 2036 financial years, connecting into the company's existing 700,000km global fibre network.

_Developers tracking infrastructure scaling for AI workloads can follow these buildouts on daily.dev._

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