The Goal

Grocedy set out to build a modern, intelligent grocery marketplace — one that could power real-time product discovery, fast fulfillment, and AI-driven recommendations at scale. To do this, they needed an architecture capable of handling rapid growth, unpredictable traffic spikes, and AI workflows without downtime.

Cognetiks partnered with Grocedy to design a cloud-native, multi-AZ, AI-enabled platform built for speed, resilience, and continuous innovation.

The Challenge

Grocedy’s initial platform couldn’t keep up with growing user demand or support AI-driven engagement:

Grocedy needed more than a migration – they required a full modernization and AI-powered redesign aligned with AWS innovation best practices.

Discovery & Assessment

Cognetiks conducted a full evaluation of Grocedy’s architecture, workloads, and operational gaps.

This resulted in a modernization roadmap mapped directly to AWS best practices and Grocedy’s growth targets.

The Solution

Cognetiks designed a cloud-native, multi-AZ architecture built for performance, reliability, and AI-driven innovation. The new platform runs on Amazon ECS Fargate for serverless container workloads, backed by a Multi-AZ Amazon RDS PostgreSQL database for resilience and Amazon Elasticache for ultra-fast search and caching. Amazon Bedrock powers Grocedy’s AI capabilities, including recommendations and knowledge-base ingestion.

To support rapid releases, we introduced a fully automated pipeline using GitHub, Terraform, CodePipeline, and CodeBuild, enabling infrastructure provisioning and application deployments with no manual steps. CloudFront, API Gateway, and private VPC networking improved application performance and security, while Secrets Manager and IAM governance strengthened access control across the stack.

What We Delivered

We transformed the monolithic application into containerized services, built reusable Terraform modules for all infrastructure components, and established a reliable Multi-AZ foundation for the platform. Grocedy’s recommendation engine was redesigned using Amazon Bedrock, and new observability dashboards were introduced through CloudWatch to provide real-time visibility into performance and system health.

The entire deployment process was automated end-to-end, enabling faster releases and eliminating downtime. The migration was completed without disruption to users, with a carefully executed database transition, warm-up of caching layers, and phased traffic cut-over to new ECS tasks.

Impact

The new platform significantly improved reliability, speed, and scalability. Downtime dropped by 96%, API response times improved by almost half, and infrastructure costs reduced by 30% thanks to efficient autoscaling. Deployment frequency increased tenfold, while operational workload for the engineering team fell by 40%.

On the business side, customer satisfaction increased by 35%, monthly active users grew by 60%, and order processing became more than twice as fast. Vendor onboarding also accelerated, enabling Grocedy to expand into new locations with far less friction.

Experience Improvements

With the new architecture, users now enjoy faster product discovery, highly personalized recommendations, smoother checkout flows, and consistent reliability even during peak grocery periods. Vendors benefit from better performance and quicker onboarding, while the internal team can roll out new features without fear of causing downtime.

Why It’s Innovative

This project represents a full transformation—from a single-node monolith to an AI-ready, cloud-native platform running across multiple Availability Zones. The combination of Amazon Bedrock, fully automated GitHub-driven deployments, and a modern microservices architecture positions Grocedy for rapid expansion and continuous innovation. The results reflect AWS-aligned excellence in automation, resilience, AI integration, and measurable business impact.