Enlight Metals Unveils Agentic AI Platform for Smarter Supply Chains

Enlight Metals launches an agentic AI platform to automate procurement, sourcing, and logistics decisions, improving accuracy, traceability, and operational efficiency.

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CIOL Bureau
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Enlight Metals Pvt. Ltd., an AI-driven metal aggregator, has introduced an agentic AI-powered operational chatbot designed to streamline procurement, sourcing, and logistics decisions across India’s industrial metals supply chain.

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Developed by Enlight Lab, the company’s research division, the platform is built to interpret operational intent, automate decision execution, and coordinate workflows without human intervention—moving beyond standard conversational automation.

Reducing Manual Effort, Improving Workflow Speed

During early adoption, Enlight Metals recorded:

  • 80% of operational queries resolved within 5 minutes

  • 60%+ automation of routine procurement and logistics tasks

  • 40% improvement in inventory forecasting accuracy

  • 50% reduction in manual validation checks

  • End-to-end traceability from demand signal to material delivery

The system continuously monitors demand patterns, predicts disruptions, reallocates sourcing, and updates stakeholders, functioning as a 24×7 operational control layer.

A Cognitive Leap for Supply Chain Decisioning

The industrial metals sector generates vast operational data, yet decision-making often remains manual and fragmented. Enlight’s platform attempts to close this gap using real-time intelligence. “Industrial metals do not lack data; they lack actionable intelligence,” said Dhananjay Goel, Director, Enlight Metals Pvt. Ltd. “Our Agentic AI compresses the gap between insight and action, enabling continuous learning and self-optimisation to elevate metal supply operations into a cognitive system.”

By integrating directly with CRM, ERP, and logistics systems, the platform enables autonomous coordination across supply workflows. Enlight Metals positions it as an early step toward a future where procurement and delivery adapt dynamically, minimising bottlenecks and operational friction.