PacketFabric and Massed Compute now offer a single, on‑demand platform that combines GPU‑as‑a‑Service (GPUaaS) with Network‑as‑a‑Service (NaaS). The integrated solution lets enterprises instantly provision high‑performance GPU compute alongside a programmable, high‑capacity network, eliminating separate contracts and manual provisioning while enabling AI workloads to scale quickly and cost‑effectively and improve overall project timelines.
Key Benefits of the Integrated Platform
Unified Provisioning
Customers use PacketFabric’s self‑service portal to size, order, and spin up GPU resources and the associated network paths in one workflow, removing the need for parallel procurement processes.
Accelerated Time‑to‑Value
The combined service shortens lead times from weeks to minutes, allowing AI teams to move from experimentation to production without waiting for network or compute contracts to be finalized.
Core Features and Use Cases
The platform supports a broad set of GPU‑intensive scenarios, delivering both compute power and low‑latency connectivity in a single package.
- Model training – Large‑scale deep‑learning jobs that require massive matrix and vector computations.
- Inference – Low‑latency serving of trained models for real‑time decision making.
- Data‑heavy analytics – Workloads that move terabytes of data between cloud and on‑premises environments.
- Hybrid AI architectures – Configurations that span multiple clouds, colocation sites, and edge nodes.
How the Service Works
Self‑Service Portal
Through an intuitive dashboard, users select GPU instance types, define network bandwidth, and launch the complete environment with a single click, receiving automated provisioning of both compute and transport layers.
Sales‑Assisted Option
For complex deployments, a sales‑assisted model provides guided design, managed GPU clusters, and on‑premises integration support, ensuring enterprise‑grade reliability and compliance.
Business Impact for Enterprises
By delivering GPU compute and high‑speed networking as a unified service, the partnership offers tangible operational and financial advantages.
- Reduced time‑to‑value – Spin up a full AI environment in minutes rather than weeks.
- Lower operational overhead – One vendor and portal simplify procurement, billing, and support.
- Scalable cost model – Pay‑as‑you‑go pricing aligns expenses with actual workload demand, avoiding over‑provisioning.
- Performance consistency – Co‑located compute and network resources minimize latency and jitter, critical for distributed training and real‑time inference.
Future Outlook
If adoption grows, the integrated GPUaaS + NaaS model could become the new standard for AI infrastructure procurement, encouraging other providers to bundle compute and networking services. This shift may accelerate hybrid AI architectures, where workloads seamlessly span a mesh of compute and network resources optimized for performance and cost.
