TCS and Qualcomm Collaborate to Develop AI-Driven Smart, Sustainable Capabilities for Industries
Tata Consultancy Services and Qualcomm are joining forces in Bengaluru to accelerate the shift toward Software Defined Everything (SDx) and on-device artificial intelligence. Their new co-innovation lab is designed to help enterprises build smarter, more sustainable systems that run at the edge—closer to where data is generated—bringing faster decisions, lower costs, and real-time responsiveness across critical sectors.
A lab purpose-built for the edge
Situated in India’s tech hub, the facility plugs into TCS’s IoT-focused “Bringing Life to Things” network and is outfitted with a private 5G setup and advanced test infrastructure. The goal is rapid prototyping and seamless scaling, using an SDx approach to decouple capabilities from hardware and deploy intelligence where it makes the most impact: on devices, on premises, and in the field.
Initial focus areas include security and surveillance, healthcare, smart infrastructure, and manufacturing—sectors where latency, reliability, and cost efficiency can make or break operations. By leveraging Qualcomm’s edge-ready platforms alongside TCS’s SDx stack, the lab aims to deliver compact, energy-efficient solutions that are configurable, secure, and built for continual evolution.
Why it matters
- Real-time decisions: Edge AI trims round trips to the cloud, enabling autonomous devices to react instantly on factory floors, in hospitals, or across critical infrastructure.
- Resilience and agility: SDx architectures simplify updates, orchestration, and security, helping enterprises adapt quickly to changing processes and standards.
- Lower total cost: Running optimized models on affordable, power-efficient edge hardware reduces bandwidth needs and cloud compute spend.
- Sustainability baked in: Smarter workloads at the edge and targeted data movement can cut energy usage while improving throughput.
From demo to deployment
The partnership builds on a history of large-scale engineering and IT programs between the two companies. In a recent proof point, TCS delivered a real-time visual inspection system for an automotive manufacturer that analyzed live camera feeds via a Qualcomm-powered edge device. The setup flagged minute surface defects—on steel and painted materials—with around 90% accuracy, and did so without sending heavy video streams to the cloud. It’s a blueprint for how affordable edge hardware can elevate quality control in industrial, aerial, or terrestrial inspections.
What they plan to build
The lab will incubate solutions that blend SDx with Edge AI across a broad footprint:
- Intelligent medical devices that support bedside inference and proactive alerts, reducing response times in care settings.
- Industrial handhelds for technicians, combining computer vision and sensor fusion to safely control machinery and validate workflows.
- Smart infrastructure capable of self-diagnosis, predictive maintenance, and adaptive resource management.
- Advanced safety and surveillance with on-device analytics for anomaly detection, privacy-first processing, and event triage.
Under the hood, TCS’s SDx approach enables a fabric of microservices, intelligent controls, and prognostics that can host AI models and agents at the edge. This foundation streamlines rollout of next-generation networks and automation, helping enterprises harden resilience while simplifying lifecycle management for fleets of devices.
The XR and spatial computing angle
For AR/VR and spatial computing, this move is timely. Private 5G and on-device AI unlock lower-latency experiences for remote assistance, guided workflows, and digital twins. Imagine technicians wearing lightweight AR headsets that recognize parts, validate procedures, and stream just-enough data to collaborators—all powered by on-site inference. As compute shifts to edge nodes and devices, immersive tools can become more responsive, reliable, and battery-friendly, making enterprise XR deployments more viable at scale.
Leaders’ outlook
Executives from both companies frame the initiative as a pragmatic path to real-world impact. Qualcomm’s leadership emphasizes cost-effective, scalable edge solutions tailored to rapidly modernizing industries, while TCS underscores its commitment to investing in AI-driven platforms that deliver agility and long-term business value. The shared vision centers on adaptive, sustainable systems that bridge physical and digital operations through secure, service-oriented architectures.
Bottom line
The Bengaluru co-innovation lab is set to become a proving ground for SDx and edge-native AI that can be deployed quickly, managed intelligently, and scaled globally. If the early results in visual inspection are any indication, expect a steady cadence of domain-specific solutions—from healthcare to manufacturing—that translate AI breakthroughs into measurable productivity and quality gains. For enterprises exploring immersive tech, digital twins, and spatial workflows, the timing couldn’t be better.
