Ekak's AI Reduces Material Wastage in Indian Manufacturing

In an exclusive interview with CXOToday, Shashank Misra, Founder & Director of Ekak Innovations, shared how his company is revolutionizing the Indian manufacturing sector with AI. One significant project involved a tech-enabled manufacturer in the flexible packaging industry, where manual precision in cutting and material handling is critical but prone to wastage and throughput variability.

Industry data shows that manual cutting in such setups can result in wastage rates of 8–12%, compared to sub-5% in fully automated lines (Export-Import Bank of India, 2022). To address this, Ekak deployed a computer vision system that detects and counts individual material pieces with over 95% accuracy, flags defective cuts in real-time, and tracks pieces per minute with second-level time stamps.

This system provided continuous data streams, enabling trend analysis across shifts and production cycles, real-time equipment-level efficiency metrics, and root-cause insights into breakdowns and slowdowns. By embedding AI within existing workflows, the plant moved toward a predictive and data-rich operational model, improving material efficiency and operator coordination without disrupting production.

Misra highlighted the key challenges Ekak faces when implementing AI in traditional Indian industries, such as trust, legacy systems, and context-adaptation. To overcome these, Ekak follows three principles: building with, not for, the client; keeping the AI invisible and robust; and proving outcomes through tangible results. The team often serves as translators between the language of AI systems and industrial intent.

Misra’s experience at Imperial College London played a crucial role in the foundation and development of Ekak Innovations. Imperial’s blend of engineering rigor with real-world application and global mindset instilled in him the importance of seeing the world as systems, not silos. This approach is at the heart of Ekak, which builds AI systems that are technologically sophisticated but operationally empathetic, especially in Indian contexts often underserved by one-size-fits-all digital solutions.

In terms of trends in specialized AI adoption within India’s industrial sector, Misra noted a shift from AI as a buzzword to AI as embedded infrastructure. Significant trends include edge-first AI for low-connectivity sites, task-specific vision models for monitoring labor, safety, and inventory, traceability systems for compliance and ESG, and agentic interfaces for non-technical teams. This shift will lead to a digitally discoverable industrial economy, where small and medium enterprises can participate in global value chains through credibility, data, and transparency.

AI in India’s industrial context is about making operations visible, measurable, and dignified, not about replacing jobs. It’s about enhancing the capabilities of existing processes and ensuring that scientific innovation serves people and is values-led.