A global chemical innovator optimized operations and accelerated insights with Cloud-Native AI

In today’s competitive chemical industry, operational agility and data-driven decisions are key to sustainable growth. This customer story highlights how a global chemical leader harnessed AWS cloud and AI technologies to unify their manufacturing data, enhance compliance, and boost innovation across multiple business units, driving significant cost savings and efficiency gains.

Customer Overview

This multinational chemical manufacturer operates across diverse sectors such as mobility, healthcare, packaging, and next-generation materials. With a commitment to sustainability and cutting-edge technology, the company sought to modernize its manufacturing infrastructure in India to support rapid growth and evolving market demands.

Challenges | Overcoming fragmented systems and data barriers

Our customer was facing growing operational inefficiencies due to data fragmentation, legacy infrastructure, and disconnected workflows across multiple business units.

• Fragmented data systems: Data from production plants, labs, and logistics existed in disconnected silos, preventing unified analytics and slowing decision-making due to manual reporting and inconsistent data formats.
• Limited scalability and agility: On-premise systems could not handle growing IoT and sensor-driven data volumes. Infrastructure constraints led to performance bottlenecks, high maintenance costs, and reduced innovation capacity.
• Data security and compliance complexity: Maintaining ISO, GxP, and environmental compliance across disparate legacy systems was difficult, requiring manual audits and exposing the organization to potential regulatory risks.
• Restricted innovation and collaboration: Isolated data environments prevented collaboration between R&D, production, and business teams, slowing new material development and responsiveness to market needs.
• Limited workforce empowerment: Decision-makers lacked access to timely insights due to outdated manual reporting. This reduced operational responsiveness and limited the workforce’s ability to act proactively on quality or performance issues.

Solution | Driving transformation with Cloud-Native data modernization

To overcome legacy inefficiencies and enable intelligent operations, the customer partnered with our team to implement an AWS-powered data modernization solution.

• End-to-end data centralization: Consolidated structured (ERP, MES, LIMS) and unstructured (sensor logs, lab reports) data on Amazon S3, with AWS Glue cataloging and preparing data for analytics across business units.
• Automated data workflows: Deployed AWS Lambda and AWS Step Functions to automate ingestion, transformation, and processing pipelines. This reduced manual intervention, enabling responsive, event-driven data flows.
• AI-ready and predictive analytics foundation: Leveraged Amazon SageMaker and AWS Bedrock to establish a framework for future AI and ML-driven use cases such as predictive maintenance, process optimization, and sustainability modeling.
• Regulatory-grade security and compliance: Implemented enterprise-grade security through AWS IAM, AWS KMS, and AWS CloudTrail for encryption, access governance, and continuous audit readiness in accordance with ISO and GxP standards.
• Scalable and sustainable infrastructure: Incorporated Amazon EC2 Auto Scaling, Amazon RDS, and AWS Backup for high availability and fault tolerance, while also enabling efficient energy usage and sustainability reporting.

Success metrics

This AWS-powered modernization initiative delivered measurable operational, financial, and strategic benefits. By integrating automation, analytics, and AI across core processes, our customer achieved faster decision-making, improved efficiency, and stronger compliance.

• 15-20% Manufacturing efficiency improvement: Optimized operations led to reduced downtime and increased throughput in production lines.
• 50-60% Compliance reporting automation: Automated data trails and audit readiness cut manual compliance effort by more than half.
• 2-3x Faster decision-making: Real-time dashboards and predictive analytics enabled quicker and more informed management decisions.
• 100% Complete data integration: Achieved unified access to data from manufacturing, R&D, procurement, and logistics domains on a single cloud platform.
• ‍10-15% Sustainability metrics improvement: Data-driven energy optimization and waste reduction supported environmental targets and responsible manufacturing.