AI-Powered Dynamic Fuel Pricing Platform

Background

Tata Elxsi implemented an AI-driven fuel pricing intelligence platform on AWS to modernize competitor price monitoring and pricing decision workflows across a large retail fuel network. The solution enabled real-time ingestion of pricing feeds from multiple external and internal data sources, centralized analytics, and AI-assisted pricing recommendations for geographically distributed retail outlets. 

Built on AWS-native services, the solution integrates secure ingestion, scalable compute, centralized data storage, and automated pipelines. It establishes a robust, cloud-native foundation for pricing intelligence, improving operational efficiency while supporting future predictive pricing and dynamic pricing optimization capabilities across the enterprise.

Challenge

A leading fuel retail enterprise operating a large network of retail outlets across India faced challenges in monitoring and responding to competitor fuel pricing changes in near real time. Pricing decisions were dependent on fragmented data collection mechanisms and manual interventions, resulting in delays,inconsistencies, and reduced responsiveness to local market dynamics.

The organization required a scalable, cloud-native platform capable of ingesting pricing feeds from multiple external and internal sources, processing them in near real time, and enabling AI-driven pricing recommendations across geographically distributed retail outlets.

The customer also required the platform to support:

• High-frequency API integrations ​
• Scalable analytics workloads ​
• Centralized monitoring and reporting ​
• Secure and resilient AWS-native deployment ​
• Faster rollout across regions without infrastructure bottlenecks ​

Solution

Tata Elxsi designed and implemented a real-time pricing data platform on AWS to address these challenges through secure ingestion, centralized architecture, and AI-driven analytics. The solution leveraged Tata Elxsi’s TEDAx accelerator to enable faster deployment of pricing intelligence, analytics, monitoring, and operational visibility capabilities across a large-scale retail fuel network.A scalable ingestion layer was built using Amazon API Gateway and AWS Lambda to process competitor pricing feeds and external market data across multiple regions. This enabled near real-time visibility into market pricing trends and reduced dependency on manual data aggregation. Pricing analytics and recommendation services were hosted on Amazon EC2, enabling advanced processing and AI-driven insights to support intelligent pricing decisions and improve pricing accuracy. 

A centralized data architecture was implemented using Amazon RDS PostgreSQL for transactional and operational data, while Amazon S3 was used for storing historical pricing datasets and analytics outputs. For secure and optimized access, Amazon CloudFront and Route 53 enabled low-latency delivery of dashboards and APIs across regions, while AWS WAF secured internet-facing endpoints. 

Operational monitoring, governance, and automation were enabled through Amazon CloudWatch, AWS CloudTrail, and AWS CodePipeline, supporting centralized observability and automated CI/CD deployments. The platform also established a scalable foundation for future predictive pricing and dynamic pricing optimization across the enterprise.

Impact

The solution enables a scalable, cloud-native pricing platform supporting over 36,000 retail outlets across regions, improving responsiveness to dynamic market conditions by ~40% and enabling quicker reactions to competitor pricing changes. It facilitates faster rollout of pricing updates, ensuring consistency and accuracy across geographically distributed locations. 

By centralizing pricing governance, the platform enhances operational agility and streamlines decision-making processes. Additionally, with ~3x improvement in API processing throughput and a resilient multi-AZ architecture with auto-scaling capabilities, the solution delivers reliable, high-performance operations, supporting seamless scalability and enterprise-wide execution.

Services Rendered

• AWS Architecture Design
• Real-Time Data Pipelines
• AI & Analytics Enablement
• RDS PostgreSQL Optimization
• CI/CD Automation
• Cloud Security & IAM
• Monitoring & Observability
• Production Support​