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What is the story about?
Alstom is using artificial intelligence to accelerate signalling engineering and maintenance processes in India, with an AI-driven system that can analyse software logs and diagnostic events in less than two hours — a task that previously took engineers up to two weeks.
Puneet Srivastava, Managing Director, Signalling and Infrastructure, Alstom India, told CNBC-TV18 that improving productivity through automation and AI has become a key focus as the company looks to deliver projects faster amid rising demand.
“Someone who was working for weeks, he can finish in hours,” Srivastava said, explaining how AI is being used to analyse large volumes of system logs, identify potential failures and enable corrective action before an issue occurs.
According to Alstom, the AI-enabled solution has already been deployed and is being scaled across its operations.
Srivastava said automation is being applied across the signalling engineering process, from capturing requirements through to the final safety release. While some processes use conventional automation and scripting, AI is being deployed where large volumes of data can be leveraged to improve productivity.
The use of AI, however, remains subject to the stringent safety requirements of railway signalling. Srivastava said Alstom uses cloud-based solutions only within closed networks for safety-critical applications, rather than exposing such systems to the public cloud.
India emerges as global signalling engineering hub
India has also emerged as a major engineering base for Alstom's global signalling business, with around 4,000 employees working in signalling in the country.
Srivastava said around 30% of Alstom's global signalling engineering work is carried out from India. Of the work undertaken by the Indian signalling engineering team, around 35% is focused on domestic projects, while the remaining 65% supports projects in global markets.
“India is already the beating heart of Alstom’s global signalling and digital innovation,” the company said.
Alstom India is currently working on signalling, services and rolling stock projects across the country, including the Namo Bharat Regional Rapid Transit System and metro networks in Delhi, Mumbai and Bengaluru.
The company has said it plans to continue investing in talent and infrastructure in India as it expands its role as an engineering and digital technology hub for its global operations.
€108 billion global backlog
At the global level, Alstom has an order book of around €108 billion, according to Srivastava. With annual sales of approximately €20 billion, the backlog provides roughly five years of revenue visibility, the company said.
While the company does not disclose the value of its regional order book, Alstom India said it has a strong commercial pipeline across its product lines and is executing several large signalling, services and rolling stock projects.
Alstom evaluating Kavach opportunity
Alstom is also evaluating opportunities under India's Kavach automatic train protection programme, although the company has yet to commit to a specific solution.
Srivastava said Alstom is currently analysing the programme as Indian Railways continues to evolve the standards. He said Railways is also in discussions with Alstom and that the company remains in the evaluation stage.
“We are still evaluating, and maybe we can come up with some solution,” Srivastava said, adding that Kavach remains on the company's radar.
Productivity key to faster project delivery
Srivastava said the push towards automation is being driven partly by the need to deliver projects within tighter timelines.
He said that while project plans may initially provide for a certain amount of time, companies increasingly have to deliver projects in significantly shorter periods, making productivity improvements critical.
For Alstom, that means automating processes across the signalling lifecycle rather than focusing on a single stage.
The company is also dealing with project-specific requirements, integration with infrastructure and rolling stock from different manufacturers, testing and validation, and changes in site conditions - all of which can require software configuration and iterations before a system is ready for deployment.
Puneet Srivastava, Managing Director, Signalling and Infrastructure, Alstom India, told CNBC-TV18 that improving productivity through automation and AI has become a key focus as the company looks to deliver projects faster amid rising demand.
“Someone who was working for weeks, he can finish in hours,” Srivastava said, explaining how AI is being used to analyse large volumes of system logs, identify potential failures and enable corrective action before an issue occurs.
According to Alstom, the AI-enabled solution has already been deployed and is being scaled across its operations.
Srivastava said automation is being applied across the signalling engineering process, from capturing requirements through to the final safety release. While some processes use conventional automation and scripting, AI is being deployed where large volumes of data can be leveraged to improve productivity.
The use of AI, however, remains subject to the stringent safety requirements of railway signalling. Srivastava said Alstom uses cloud-based solutions only within closed networks for safety-critical applications, rather than exposing such systems to the public cloud.
India emerges as global signalling engineering hub
India has also emerged as a major engineering base for Alstom's global signalling business, with around 4,000 employees working in signalling in the country.
Srivastava said around 30% of Alstom's global signalling engineering work is carried out from India. Of the work undertaken by the Indian signalling engineering team, around 35% is focused on domestic projects, while the remaining 65% supports projects in global markets.
“India is already the beating heart of Alstom’s global signalling and digital innovation,” the company said.
Alstom India is currently working on signalling, services and rolling stock projects across the country, including the Namo Bharat Regional Rapid Transit System and metro networks in Delhi, Mumbai and Bengaluru.
The company has said it plans to continue investing in talent and infrastructure in India as it expands its role as an engineering and digital technology hub for its global operations.
€108 billion global backlog
At the global level, Alstom has an order book of around €108 billion, according to Srivastava. With annual sales of approximately €20 billion, the backlog provides roughly five years of revenue visibility, the company said.
While the company does not disclose the value of its regional order book, Alstom India said it has a strong commercial pipeline across its product lines and is executing several large signalling, services and rolling stock projects.
Alstom evaluating Kavach opportunity
Alstom is also evaluating opportunities under India's Kavach automatic train protection programme, although the company has yet to commit to a specific solution.
Srivastava said Alstom is currently analysing the programme as Indian Railways continues to evolve the standards. He said Railways is also in discussions with Alstom and that the company remains in the evaluation stage.
“We are still evaluating, and maybe we can come up with some solution,” Srivastava said, adding that Kavach remains on the company's radar.
Productivity key to faster project delivery
Srivastava said the push towards automation is being driven partly by the need to deliver projects within tighter timelines.
He said that while project plans may initially provide for a certain amount of time, companies increasingly have to deliver projects in significantly shorter periods, making productivity improvements critical.
For Alstom, that means automating processes across the signalling lifecycle rather than focusing on a single stage.
The company is also dealing with project-specific requirements, integration with infrastructure and rolling stock from different manufacturers, testing and validation, and changes in site conditions - all of which can require software configuration and iterations before a system is ready for deployment.
