Blog | nearby computing

Implement AI Without Falling into Multicloud Chaos

AI is accelerating faster than infrastructure strategies can keep up

Over the past year, enterprises have raced to integrate artificial intelligence into their operations. From automating customer service to powering advanced analytics and generative AI, the momentum is undeniable. Yet behind this wave of innovation lies a growing operational burden — and multicloud complexity is emerging as one of its biggest bottlenecks.

While many organisations have adopted multicloud strategies for flexibility, resilience, and cost optimisation, these architectures were never designed with AI in mind. AI workloads are fundamentally different. They require high-performance GPUs, generate massive volumes of data, and are extremely sensitive to latency, observability, and orchestration efficiency.

This mismatch is now surfacing in critical ways:

Disjointed infrastructure across traditional hyperscalers and newer GPU-focused clouds
Rising costs due to data movement, overprovisioning, and lack of visibility
Fragmented tools and APIs that slow down operations and break automation workflows
Operational silos that hinder collaboration across DevOps, I&O, and data science teams
Gaps in skills and planning that delay scaling and increase risk

As AI initiatives grow in scope and scale, these challenges are compounding. Many organisations are finding themselves in a situation where their cloud infrastructure, once a strength, is now a barrier to progress.

Resilient systems and multivendor strategy

A new approach to AI-scale infrastructure

Implementing AI without fragmenting your environment — or losing control of costs and performance — requires a different approach.

This is where NearbyOne’s Multi-cloud Manager provides critical value.

Built specifically for today’s AI- and edge-centric infrastructures, NearbyOne enables enterprises to move beyond traditional DevOps tooling and adopt a more unified, intent-driven approach to multicloud operations.

What NearbyOne delivers

Key capabilities include:

End-to-end orchestration for both GPU workloads and general-purpose compute
No-code onboarding for applications and network functions (xNFs)
Day 0 to Day 2 automation, including provisioning, configuration, and lifecycle management
Real-time observability and telemetry, tailored for edge, telco and distributed environments
SLA and KPI monitoring, with centralised alarms across hybrid and edge sites
Support for multi-tenancy, role separation and federated management
Built-in cost awareness and operational governance

NearbyOne was designed from the ground up for the demands of telco-grade, distributed, and AI-powered architectures. Its modular design and intuitive UI allow infrastructure and operations teams to coordinate complex workloads across multiple clouds, locations, and business units — without requiring deep development expertise.