Indian Railways has officially joined hands with the Digital India Bhashini Division (DIBD) to implement advanced multilingual artificial intelligence technologies across its customer-facing digital infrastructure. The move is aimed at bridging language barriers for millions of passengers by deploying voice and text-based AI solutions in 22 Indian languages.
The Memorandum of Understanding (MoU), signed in New Delhi, formalises this partnership between the Centre for Railway Information Systems (CRIS) and BHASHINI, a division under the Ministry of Electronics and Information Technology (MeitY). Officials from both organisations noted that the collaboration will serve as a cornerstone for inclusive service delivery in India’s largest transportation network. The initiative will see the integration of BHASHINI’s comprehensive language stack—comprising Automatic Speech Recognition (ASR), Text-to-Text Translation, Text-to-Speech (TTS), and Optical Character Recognition (OCR)—into CRIS-managed platforms such as the National Train Enquiry System (NTES), RailMadad, and other upcoming digital interfaces. These tools will allow railway passengers to interact with essential railway information and services in their preferred Indian language, without being constrained by the existing English-dominant ecosystem.
According to railway officials, the scope of this project extends beyond simple language translation. The collaborative framework also includes the development of interactive voice-based assistance through AI-powered chatbots and speech recognition tools. These features are expected to significantly ease the journey experience for regional language speakers and non-English-literate populations, thus making the railway system more inclusive. The project is also envisioned to support multilingual voice assistance at railway counters, kiosks, mobile apps, websites, and call centres. It will serve as a transformative digital touchpoint for over 23 million daily rail passengers, most of whom communicate in vernacular languages.
Officials from CRIS highlighted that this digital transformation effort aligns with the broader Digital India mission, specifically focusing on democratising access to public services by leveraging AI and cloud technologies. The partnership reflects a conscious effort to embed language accessibility into digital governance and public infrastructure. The AI language stack, designed by BHASHINI, is cloud-compatible and can also be deployed on premise, allowing flexible implementation based on specific digital infrastructure needs. The technologies will also be integrated into real-time passenger information systems to support interactive services during journey planning, ticketing, grievance redressal, and emergency updates.
As part of the rollout strategy, joint technical workshops and pilot testing of the multilingual systems are scheduled to begin in the coming months. These pilot projects will focus on identifying user experience gaps and optimising voice-user interface technologies for a public transport environment that operates in high-noise, high-traffic conditions. This collaborative move is being hailed as a benchmark in India’s pursuit of building inclusive, AI-powered civic systems that reflect the linguistic diversity of the nation. It comes at a time when the Union government is emphasising the importance of vernacular language support across all digital public platforms, from healthcare to transportation.
Experts in language technology and public policy say this development could redefine how large-scale public utilities in India adapt to AI-driven interfaces while maintaining cultural and linguistic sensitivity. According to digital accessibility advocates, the success of this partnership could also set a precedent for other departments and sectors to adopt similar solutions, thereby multiplying the socio-economic impact of AI in governance. Moreover, this multilingual AI upgrade is aligned with the goals of creating equitable, gender-neutral, and environmentally sustainable cities. Improved communication and real-time language translation can reduce information asymmetry, improve crowd management, and ultimately foster more efficient mobility systems that require fewer physical touchpoints, thus lowering operational footprints.
From an infrastructure standpoint, the integration of language AI will require recalibration of existing systems to allow seamless interoperability between different digital platforms. The initial capital outlay is expected to be absorbed within the existing innovation and IT budgets, although scale-up might involve phased financial planning supported by MeitY and CRIS. For citizens, this means better, more personalised access to real-time train information, multilingual grievance resolution, and a boost in digital confidence among those previously marginalised due to language barriers. The collaboration is a testimony to how technological convergence can be guided by social inclusion and sustainable growth.
As this partnership progresses from MoU to execution, it is expected to generate a model that can be replicated across various government platforms such as bus transit systems, smart city dashboards, and state e-governance portals. This systemic shift promises not just a better rail experience but also a foundational step toward a multilingual digital India.
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