HCLTech VisionX 2.0 AI edge platform unveiled

HCLTech has introduced VisionX 2.0, an upgraded version of its AI edge platform designed for mission-critical industrial environments. The platform focuses on delivering real-time intelligence, operational efficiency and enhanced safety at scale.

The HCLTech VisionX 2.0 AI edge platform builds on the company’s Intelligent Secure Edge capabilities. It integrates computer vision, vision language models, multi-modal data fusion and edge-optimised generative AI within a unified framework for industrial use cases.

Built for industrial edge intelligence

VisionX 2.0 is purpose-built for demanding operational environments where latency, reliability and data security are central. It supports on-premise deployment to enable real-time inference directly at the edge.

The platform runs on NVIDIA Jetson systems, NVIDIA RTX PRO 6000 Blackwell GPUs and Dell NativeEdge deployments. By processing data locally, it addresses bandwidth constraints, maintains data privacy and supports sensitive industrial operations.

The integration of the NVIDIA physical AI computing stack includes:

• NVIDIA Blueprint for video search and summarisation

• NVIDIA DeepStream

• NVIDIA Cosmos Reason VLM

• NVIDIA TAO for post-training vision models

This combination allows the platform to handle high-performance AI workloads in distributed industrial settings.

Multi-modal AIoT engine at the core

A key component of the HCLTech VisionX 2.0 AI edge platform is its multi-modal AIoT engine. The system analyses inputs from:

• Video feeds

• Audio streams

• Images

• LiDAR

• Stereo cameras

• IoT telemetry

By combining these data streams, the platform can detect anomalies, safety violations, operational risks and events with improved contextual understanding.

The inclusion of vision language models and multi-modal fusion enables scene-level interpretation rather than simple object detection. This expands the system’s ability to support decision-making in complex environments.

Event verification and reasoning layer

VisionX 2.0 introduces a video search and summarisation event reviewer. Selected computer vision clips are routed to Cosmos Reason to identify false positives and apply additional natural language processing-based reasoning.

This verification layer is intended to increase reliability in event detection and provide deeper contextual insights before triggering action. The goal is to reduce noise and improve operational confidence in automated monitoring systems.

Zero-trust architecture for distributed sites

Security is integrated at the architectural level. The HCLTech VisionX 2.0 AI edge platform features a zero-trust framework and zero-touch provisioning on Dell NativeEdge OS.

This approach supports secure and scalable rollouts across distributed industrial sites. It also ensures that edge deployments remain aligned with enterprise security standards while operating in remote or sensitive environments.

The platform is compatible with existing cameras, video management systems and sensors through a flexible integration layer. This allows enterprises to deploy the solution without replacing existing infrastructure.

Executive perspectives

Vijay Guntur, CTO and Head of Ecosystems at HCLTech, said the platform combines secure edge engineering expertise with NVIDIA AI infrastructure and models. He noted that the system is designed to move enterprises from reactive monitoring towards real-time, trusted decision-making.

Deepu Talla, Vice President, Robotics and Edge AI at NVIDIA, said the next phase of industrial transformation is driven by real-time, multi-modal intelligence. He added that the platform provides enterprises with a foundation to deploy high-performance AI at the industrial edge.

Position within broader Physical AI strategy

VisionX 2.0 forms part of HCLTech’s broader Physical AI portfolio. This portfolio integrates Kinetic AI, cognitive robotics, autonomous systems and edge AI to improve productivity, resilience and sustainability in operational environments.

The HCLTech VisionX 2.0 AI edge platform represents a continued focus on bringing advanced AI capabilities closer to industrial assets. Instead of centralised processing alone, intelligence is embedded at the edge where milliseconds can influence outcomes.

For enterprises operating in high-risk or high-value environments, the platform signals a shift toward distributed, multi-modal AI systems designed for real-time operational control.

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