HCLTech has introduced VisionX 2.0, the latest iteration of its multi-modal AI edge platform developed in collaboration with NVIDIA. The enhanced platform is designed to deliver real-time insights, improved safety and greater operational efficiency across mission-critical industrial settings. VisionX 2.0 builds on HCLTech’s Intelligent Secure Edge framework, combining advanced computer vision, vision-language models (VLMs), multi-modal data fusion and edge-optimized generative AI.
The platform leverages NVIDIA’s physical AI computing stack, including NVIDIA Blueprint for video search and summarization (VSS), NVIDIA DeepStream, NVIDIA Cosmos Reason and NVIDIA TAO to deliver high-performance processing for industrial environments.
Designed to address demanding industrial environments, VisionX 2.0 brings a comprehensive set of advanced capabilities that strengthen performance, security and operational intelligence at the edge. The platform is purpose-built to support complex, high-stakes use cases where real-time responsiveness and reliability are critical.
At the core of the solution is powerful on-premises edge AI processing, driven by NVIDIA Jetson modules, NVIDIA RTX PRO 6000 Blackwell GPUs and deployments through Dell NativeEdge. This architecture enables real-time inference directly at the edge, reducing reliance on cloud connectivity, easing bandwidth pressure and safeguarding sensitive operational data.
VisionX 2.0 also features a robust multi-modal AIoT engine capable of analyzing diverse data streams, including video, audio, images, LiDAR, stereo camera feeds and IoT telemetry. By correlating these inputs, the platform detects anomalies, safety violations and emerging risks with a high degree of accuracy, enabling faster and more informed interventions.
To enhance reliability, the VSS Event Reviewer evaluates selected computer vision clips using NVIDIA Cosmos Reason. This process helps eliminate false positives and applies advanced language-based reasoning to generate deeper scene-level insights, strengthening decision-making confidence across operational teams.
Security and scalability are embedded into the platform through a Zero-Trust architecture and Zero-Touch Provisioning enabled by Dell NativeEdge OS. Additionally, a flexible integration layer ensures seamless compatibility with existing cameras, Video Management Systems (VMS) and sensors, allowing organizations to upgrade capabilities without extensive infrastructure changes.
“With VisionX 2.0, we are transforming how intelligence operates at the industrial edge,” said Vijay Guntur, CTO and Head of Ecosystems at HCLTech. “By combining our secure edge engineering capabilities with NVIDIA’s AI infrastructure and models, we are helping enterprises shift from reactive monitoring to real-time, trusted decision-making. The platform supports safer operations, improved efficiency and scalable AI adoption while maintaining strong security and performance standards.”
Deepu Talla, Vice President of Robotics and Edge AI at NVIDIA, added, “The next phase of industrial transformation is powered by Physical AI—real-time, multi-modal intelligence that enhances performance, safety and autonomy across operations. By integrating NVIDIA Metropolis and NVIDIA Omniverse, VisionX 2.0 provides a scalable foundation for deploying high-performance AI at the industrial edge.” HCLTech’s Physical AI portfolio combines Cognitive Robotics, Autonomous Systems and Edge AI technologies to strengthen productivity, resilience and sustainability across real-world industrial environments.
HCLTech is a global technology company with more than 226,300 employees across 60 countries. The company delivers capabilities spanning AI, digital, engineering, cloud and software services, supported by a broad portfolio of technology solutions. HCLTech serves clients across Financial Services, Manufacturing, Life Sciences and Healthcare, High Tech, Semiconductor, Telecom and Media, Retail and CPG, Mobility and Public Services. For the 12 months ending December 2025, the company reported consolidated revenues of $14.5 billion.
