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Manufacturing
Amazon S3, Amazon SQS, Amazon Bedrock, AWS Lambda, Amazon Athena, Amazon SNS
Automated scheme letter processing with enhanced validation, reduced effort, and faster processing
Established as part of a major industrial group’s diversification into the paints industry, the company has rapidly emerged as a modern, technology-driven brand committed to transforming the decorative and industrial coatings market in India. Headquartered in Mumbai, the company emphasizes transparency, innovation, and customer-first principles in its product and service offerings.
Improvement in Data Processing Speed
Improved Accuracy
Reduction in Manual Effort
The paint manufacturing company faced operational inefficiencies in processing scheme letters and calculating dealer bonuses due to documents in various formats requiring manual data extraction. Without intelligent OCR, frequent errors occurred in identifying product names, bonus slabs, and regions, while product naming variations complicated validation against master datasets. These mapping errors affected bonus computations, causing delays, disputes, and payout inconsistencies. Heavy manual effort was required for generating transactional files, necessitating an automated solution to extract accurate data from unstructured documents while reducing turnaround time and operational dependencies.
• Implemented automated ingestion workflow for scheme letters (PDF/JPG/PNG/JPEG) and datasets in Amazon S3, triggering OCR processing pipeline
• Developed AWS Lambda functions for file preprocessing and Amazon Bedrock Claude Sonnet model invocation to extract structured OCR data
• Built a two-step validation engine using AWS Lambda to match extracted product names and regions with master datasets using fuzzy similarity checks
• Designed AWS Glue Crawlers and ETL Jobs to detect processed OCR files, update Data Catalog, and transform results into transactional and bonus calculation files
• Implemented JSON-based mapping framework to resolve product naming variations and apply correct bonus logic for OCR-extracted names
• Stored and transformed outputs, including transactional files, similarity results, and bonus datasets, in Amazon S3 for downstream reporting
• Enabled business users to query validated data using Amazon Athena for serverless SQL-based analytics and insight generation
• Integrated Amazon SNS for alerting on AWS Glue job failures and real-time pipeline monitoring
Transformed scheme letter processing through end-to-end automation, achieving 90% mapping accuracy, 70% manual effort reduction, 5× processing speed improvement, and 60% operational support reduction with proactive monitoring.
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