Mane Kancor, a leader in natural food ingredient extraction and production, struggled to optimize raw material concentration to meet desired specifications without increasing production time. This inefficiency led to aged inventories, raw material degradation, and suboptimal utilization, impacting future orders and overall efficiency.

We implemented an enterprise-wide framework to enhance order planning, raw material utilization, and AI-assisted blend planning. Our hybrid architecture included:

•Data Ingestion Layer – Secure, orchestrated data jobs from on-prem data centers, maintaining data integrity.

•Data Processing Layer – Scalable pipelines to process high-volume data swiftly, ensuring timely availability of transactional data.

•Data Warehouse – A unified schema integrating business processes and application logic, ensuring traceability and accountability.

•Application/Service Layer – A proprietary AI model trained on business data, deployed as an inference engine for intelligent blend planning.

•User Interface Layer – A dedicated UI for workflow management, with enhanced security features like authentication and data masking.

AI-Powered Blend Optimization – Predictive blend concentration reduces turnaround time from production to quality assurance.

Efficient Raw Material Usage – A dynamic, rule-based engine prioritizes raw materials to prevent aged or unused inventory.

Reduced Production Lead Time – Automated, systematic execution of production orders significantly cuts lead times.

Improved Order Planning & Capacity Utilization – Enhanced planning and control ensure full utilization of production capacity.With this AI-driven approach, Mane Kancor now optimizes raw material usage, minimizes waste, and improves overall production efficiency.

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