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Applied Computing and Datasamudra Announce Strategic Partnership to Accelerate AI Deployment for the Global Energy Sector

by FWM
December 17, 2025
in National
0

PHOTO CREDIT-Teleindia Datacenter Private Limited (Datasamudra)

Tuesday, Dec 16, 2025 16:12:19

Bengaluru, December 16, 2025 – Teleindia Datacenter Private Limited (Datasamudra) has entered into a strategic partnership with Applied Computing, a British AI company building foundation models for energy operations.

The collaboration supports the secure and scalable deployment of Applied Computing’s industrial AI platforms within Datasamudra’s Tier-III compliant, AI-ready data centres in India. As part of the partnership, Applied Computing will operate its AI infrastructure within Datasamudra’s facilities, enabling high-performance, resilient deployments designed for mission-critical energy operations worldwide.

Scope of collaboration: 

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During the inauguration ceremony of Applied Computing’s new Bengaluru office at KIADB IT Park, the company outlined how the partnership will support the deployment of its industrial AI offerings for energy operations. Datasamudra will provide robust colocation and AI-enabled private cloud infrastructure, including secure facilities with guaranteed uptime, redundant power systems, advanced cooling, high-speed connectivity, and access to compute, storage, networking hardware, and GPU-as-a-Service.

At the event, Applied Computing showcased Orbital, its foundation model built specifically for the energy industry. Orbital combines time-series intelligence, physics-based validation, and large language models trained on industrial and process engineering knowledge to support reliable, explainable decision-making in complex operations.

As a foundation model built for the energy sector, Orbital supports applications across oil and gas, refining, petrochemicals, LNG, and upstream operations. By grounding AI outputs in real operational data and physical constraints, Orbital helps operators improve reliability, efficiency, and asset performance while enabling meaningful emissions reduction.

Strategic Impact: 

The partnership brings together Datasamudra’s AI-ready infrastructure with Applied Computing’s deep expertise in foundation models for energy and heavy industry. By combining high-density compute environments with production-grade industrial AI, the collaboration enables energy companies to improve operational reliability, enhance efficiency, and deploy AI confidently in mission-critical environments.

Applied Computing has formally expanded its presence in India with the inauguration of its Bengaluru office on 12 December, strengthening its ability to serve global energy customers from one of the world’s fastest-growing technology hubs.

Forward Outlook: 

Through this strategic partnership, Applied Computing will deploy and scale its AI infrastructure within Datasamudra’s state-of-the-art facilities in Bengaluru. This foundation will support the global rollout of Orbital, enabling faster, more reliable adoption of industrial AI across energy markets worldwide.

“Partnering with Datasamudra enables us to train AI models powering Orbital at industrial scale, to achieve the reliability and performance thresholds required by mission-critical energy operations” said Dr. Samyakh Tukra, CAIO, Applied Computing. “Their infrastructure provides a strong foundation for training our foundation models at scale, across global energy and heavy industry customers.”

“This partnership strengthens India’s position as a global hub for AI infrastructure,” said Mr Mahanthesh Kestur, CEO & Managing Director, Datasamudra. “Applied Computing’s industrial AI innovation, combined with our sustainable, high-performance data centre ecosystem, will accelerate digital transformation for the global energy sector.”

This strategic partnership marks a significant step in building a robust, production-grade AI ecosystem for mission-critical industrial sectors, combining Applied Computing’s global AI innovation with India’s rapidly expanding data centre capabilities.

FWM

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