A rapidly expanding digital commerce brand serving a broad consumer base across multiple product categories adopted Amazon Bedrock foundation models to deliver conversational product search, AI-generated content, and personalised recommendations, boosting engagement and increasing conversions across its online channels.

The Challenge

The customer needed to modernise its digital commerce platform with AI-driven personalisation to improve shopping experiences and boost conversions. Key challenges included:

• Reliance on a static, rules-based recommendation system that struggled to adapt to new shoppers or emerging trends.
• Need for natural language product search and generative product descriptions to improve discovery and engagement.
• Desire for customer service chatbots and personalisation without the complexity of managing large-scale ML infrastructure.

Our Solution

Rambunct implemented Amazon Bedrock to provide a generative AI layer integrated into the customer’s commerce platform, enabling dynamic personalisation at scale.

• Conversational Product Search: Bedrock foundation models enabled customers to describe products in natural language.
• Personalised Recommendations: Combined real-time session data with Bedrock-powered natural language generation for tailored suggestions.
• AI-Generated Content: Automated product descriptions that adapted tone and style to target demographics.
• Customer Support Chatbots: AI assistants embedded in the website and mobile app to reduce reliance on live agents.

The Result

The solution significantly improved engagement, conversion rates, and operational efficiency.

• 25% increase in click-through rates for recommended products.
• 15% higher sales conversions from AI-powered product search and recommendations.
• 70% reduction in content creation time through automated product description generation.
• 60% improvement in customer service response times, reducing human agent workload.

The post Driving Personalised Digital Commerce with Amazon Bedrock appeared first on Rambunct Consulting.

Casel’s Market modernised its customer engagement using Amazon Pinpoint and Amazon SES to automate personalised delivery and pickup communications, enhance community relationships, and grow repeat business, while honouring nearly a century of local service through secure, scalable marketing workflows.

The Challenge

• Manual outreach processes led to inconsistent communication about deliveries and promotions.
• Lack of customer segmentation prevented personalised, targeted engagement across services.
• Outdated tools hindered campaign scalability, analytics, and automation.
• Limited CRM integration blocked loyalty tracking, follow-ups, and feedback collection.

Our Solution

• Implemented Pinpoint for multichannel campaigns, audience segmentation, and loyalty outreach.
• Deployed Amazon SES for secure, high-deliverability transactional and promotional emails.
• Created automation workflows for Tuesday delivery, kerbside pickup, and seasonal offers.
• Integrated analytics, real-time messaging, and data governance tools for compliance and insight.

The Result

Casel’s Market gained real-time visibility, improved customer engagement, and scalable communications for continued growth and community loyalty.

• 85% increase in customer engagement via personalised messaging about services.
• 90% boost in Tuesday delivery utilisation through automated reminders.
• 70% growth in kerbside pickup adoption from timely, value-driven communications.
• 60% lift in repeat purchases through loyalty automation and targeted promotions.

The post Rambunct Boosts Casel’s Customer Engagement with Amazon Pinpoint & Amazon SES Marketing Automation appeared first on Rambunct Consulting.

UGallery, a leading online art marketplace, moved from ageing GoDaddy Windows Server 2012 R2 to a cloud-native AWS stack. The migration turned its monolithic app into a scalable, secure, maintainable platform. AWS services, VPN, and DevOps now boost security, performance, and efficiency.

The Challenge

• Obsolete & Inflexible Platform: Relied on end-of-life Windows Server 2012 R2, outdated software, and a rigid hosting environment lacking scalability and customisation.
• Security & Compliance Risks: Weak network security, no centralised access control, minimal backup/disaster recovery, and exposure to vulnerabilities.
• Performance Bottlenecks: Frequent slowdowns during peak traffic, no auto-scaling or load balancing, and poor database efficiency affected user experience.
• Operational Burdens: High manual maintenance, limited monitoring, outdated workflows, and no environment separation hindered development agility.

Our Solution

• Cloud-Native Transformation: Migrated legacy systems to containerised applications with Amazon ECS and AWS Fargate, implemented an Application Load Balancer, Amazon RDS, and auto-scaling to ensure resilience and flexibility.
• Enhanced Security & Operations: Built secure networking with VPCs, AWS IAM, AWS WAF, VPN, and centralised operations using AWS Systems Manager, AWS Backup, and AWS CloudTrail for compliance.
• Messaging, Monitoring & CI/CD: Integrated Amazon SES, Amazon SNS, Amazon SQS, and Amazon EventBridge for communication; used Amazon CloudWatch, AWS X-Ray, and Amazon Route 53 for visibility; and standardised deployments via AWS CloudFormation and CI/CD pipelines.

The Result

The migration empowered UGallery with a modern, secure, and cost-effective infrastructure, delivering measurable gains in performance, reliability, and scalability.

• Significant Performance Gains: Achieved 90% faster load times and 99.9% uptime with a CDN, optimised architecture, and automated recovery.
• Operational Efficiency & Cost Savings: Reduced overhead by 60% and cut hosting costs by 50% through managed services and automation.
• Improved Security & Scalability: Enhanced access controls, enabled secure remote work, and built scalable infrastructure to support growth and peak traffic demands.

The post UGallery: Legacy Infrastructure Migration to Cloud-Native AWS Case Study appeared first on Rambunct Consulting.