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Original article date: Jul 05, 2026

How RailYatri Achieved 60% Faster Infrastructure Provisioning Using Cloud AI

July 5, 2026
•
5 min read

When post-pandemic demand for RailYatri’s Indian train and intercity-bus booking platform surged 15–20% month over month, the company’s existing infrastructure couldn’t keep up. Legacy on-premises systems couldn’t scale fast enough, data was fragmented, and manual support workflows slowed down the customer experience.

RailYatri partnered with NTT DATA to modernize its operations on Google Cloud — and the results show what AI-powered cloud infrastructure can deliver at scale.

The Solution Stack

  • Real-time analytics: BigQuery now manages all booking and operational data, delivering instant insights across the platform.
  • Scalable infrastructure: Google Compute Engine enabled nearly 60% faster infrastructure provisioning, allowing the platform to handle traffic spikes without degrading booking performance.
  • AI-powered customer interactions: Google Cloud Speech-to-Text automated call transcription for support analysis, while Text-to-Speech handles travel updates — reducing manual effort and improving response quality.
  • Looker dashboards: Teams now monitor booking trends, revenue patterns, and service performance in real time to support data-driven decisions.

Outcomes

RailYatri now maintains 24/7 booking availability, even during India’s highest-demand travel seasons. The Advanced Resource Period feature sends real-time alerts during high-demand slots, helping passengers secure tickets faster. The platform serves travelers across 230+ cities, handling millions of searches and bookings each month.

The Broader Signal

This case illustrates a pattern playing out across travel-tech and consumer platforms globally: cloud AI infrastructure is no longer a competitive differentiator — it’s becoming the baseline for operating at scale.

Read the full article on NTT Data

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