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Improving cold-chain
management and reducing food
waste with Databricks and AI

Brief Overview

A leading grocery retailer sought to integrate intelligent automation and artificial intelligence into its fresh produce supply chain to ensure consistently high product quality across stores. The organization required a reliable technology partner with proven expertise in implementing AI-driven retail solutions. By transforming the existing data infrastructure and leveraging real-time machine learning insights, DC Tech delivered a scalable and future-ready solution that reduced operational costs, enhanced inspection accuracy and significantly improved overall supply chain efficiency.

INDUSTRY

Retail

KEY SOLUTIONS

Integrated data workflows, robust data governance, AI-driven capabilities and next-generation data infrastructure transformation.

KEY TECHNOLOGIES

Databricks, Machine Learning, AI, Cloud

MEET THE TEAM

MIKE.P

VP CONSULTING SOLUTIONS
DATA & AI

JATIN PAL

SVP BUSINESS PARTNER

RAJ KUMAR

MANAGER
SOLUTIONS DELIVERY

Discover the power of partnership

Contact us

Challenge

The grocery retailer aimed to enhance the quality and freshness of perishable goods available in its stores. However, its existing technology landscape was not designed to support real-time analytics or continuous data processing. As a result, supply chain operations were inefficient, causing unnecessary losses and reduced profitability.

Delayed operational responsiveness

The organization lacked streaming infrastructure and real-time data ingestion capabilities. This made it difficult to take immediate action when temperature-sensitive products were exposed to risks during transportation.

Data inconsistencies and structural gaps

The legacy data framework was outdated and did not follow a layered or medallion-based architecture. This limited visibility into data lineage and made it challenging to maintain consistent data accuracy and reliability.

Challenge Image
Background

Solution

To overcome these obstacles, DC Tech designed and deployed a cloud-based data ecosystem powered by Databricks. The solution incorporated real-time streaming workflows, structured datasets built on a Medallion framework and AI-powered quality assessment models that enabled inspectors to make informed decisions instantly. This end-to-end transformation strengthened cold-chain management and equipped the retailer with actionable insights to minimize spoilage risks during transportation.

This comprehensive solution optimized cold-chain operations and gave the grocer the insights needed to reduce the risk of food going bad in transit.

Data Acquisition Framework

The team built robust pipelines to collect data from both internal systems and external applications (e.g., temperature sensors, logistics platforms).

Data preparation and reporting

Data was curated, standardized and presented in accessible formats for internal stakeholders.

Data harmonization

DC tech joined data from multiple systems to create a unified Fresh Domain Data layer.

A PROGRESSIVE DATA JOURNEY

ANALYTICS

Uncover improvement opportunities

OPERATIONAL INSIGHTS

Extract meaningful next steps

REAL-TIME ADJUSTMENTS

Empower active participation in day-to-day decisions

For instance, data analysis might indicate that temperature-sensitive items such as leafy vegetables and bananas are regularly subjected to elevated temperatures while being transported from distribution hubs to retail outlets. With these insights, leadership teams can pinpoint operational gaps, initiate corrective actions and address underlying causes. This proactive approach significantly minimizes the likelihood of customers encountering spoiled or compromised fresh produce in stores.

Deliverables

Scalable supply chain intelligence

Developed and deployed a comprehensive cloud-first architecture to enable advanced, real-time analytics across the entire supply network.

Secure and governed data ecosystem

Established centralized data governance using Databricks Unity Catalog to streamline access management, enforce policies and maintain consistent metadata standards. Integrated robust validation, testing and monitoring mechanisms to preserve data integrity and reliability over time.

Optimized data processing framework

Adopted a Medallion-based architecture within Databricks, implementing Bronze, Silver and Gold layers to ensure structured processing, improved traceability and enhanced data lineage visibility.

Deliverables Image

Project outcomes

The grocery retailer effectively embedded AI into its core operations and experienced rapid results, including improved product freshness and greater efficiency across supply chain processes.

The project delivered several non-quantitative improvements:

35%

Reduction in food waste

40%

Faster operational response

25%

Improved inventory visibility

50%

Better cold-chain monitoring

Custom solutions to achieve your goals

From strategy to implementation, we provide the knowledge and leadership our clients rely on to accelerate their business. Our proven team takes a unified approach to driving large-scale change and unlocking new opportunities for growth and success.