Regal Swiss provided expert consultancy to redesign the core architecture of an AI automation platform, focusing on scalability, efficiency, and seamless integration. Our team conducted a thorough audit of the existing infrastructure, identifying bottlenecks in data processing and module interactions. We recommended a microservices-based approach using containerization with Docker and orchestration via Kubernetes, ensuring high availability and fault tolerance. Additionally, we optimized database schemas for faster query responses and implemented cloud-agnostic solutions compatible with AWS, Azure, and Google Cloud. This overhaul allowed the platform to handle increased user loads without compromising speed. Our collaborative process involved close alignment with the client's development team, incorporating agile methodologies for iterative improvements. The result was a robust, future-proof architecture that supports rapid feature deployment and reduces operational costs, positioning the platform as a leader in AI-driven automation for businesses seeking reliable, scalable solutions.
Novanode
Docker, Kubernetes, Microservices, AWS, Azure, Google Cloud
Architecture redesign consultancy
Regal Swiss cloud architecture and DevOps team
Scaling infrastructure to support growing user base and data volume
Integrating diverse AI modules without performance degradation
Ensuring compatibility across multiple cloud providers
Minimizing downtime during architectural transitions
Implemented microservices architecture with Kubernetes orchestration
Optimized database designs using indexing and partitioning techniques
Developed cloud-agnostic APIs for seamless multi-provider support
Utilized agile sprints for phased rollout and minimal disruption
Achieved 300% increase in platform scalability and user capacity
Reduced latency in AI processing by 45% through optimizations
Lowered infrastructure costs by 35% with efficient resource allocation
Enabled faster deployment of new features, boosting innovation speed