Industry: Enterprise / Regulated Cloud Environment

Challenge

The organisation needed to process high-volume, asynchronous events across multiple systems, with strict requirements for scalability, reliability, observability, and cost control.
Existing batch-based and manually operated processes were slow, fragile, and difficult to scale, leading to delayed outcomes and operational risk.

Solution

Designed and delivered a cloud-native, event-driven AI processing platform using modern DevOps and MLOps principles.

The solution included:

• Event ingestion via managed messaging queues

• Containerised AI workers running on a scalable orchestration platform

• AI-powered processing and validation logic embedded into workflows

• Secure cloud integration with storage, logging, and monitoring services

• Automated scaling and fault handling to support burst workloads

The platform was built for production reliability, cost efficiency, and future AI expansion.

Impact

• Near real-time processing of large event volumes

• Automatic scaling based on workload demand

• Reduced operational overhead and manual intervention

• Improved system reliability, observability, and fault tolerance

• Cloud costs aligned directly with actual usage