Galadriel provides an on‑demand marketplace for high‑performance GPU clusters in the US and EU, enabling AI developers and enterprises to provision NVIDIA H200, B200, and B300 accelerators instantly via web portal or API. The platform uses a pay‑as‑you‑go model with no minimum usage, auto‑scaling orchestration, and real‑time monitoring to lower total cost of ownership for training and inference workloads.
Funding
Funding not disclosed
Founders
Product
Problem
AI developers and enterprises often face high upfront costs, long-term contracts, and limited availability when trying to access large-scale GPU infrastructure for training and inference workloads. This restricts their ability to scale projects quickly and hampers revenue growth from AI services.
Solution
Galadriel offers an on-demand marketplace for high-performance GPU clusters located in the US and EU. Customers can provision accelerators such as NVIDIA H200, B200, and B300 instantly, paying only for the time they use, without committing to multi-year agreements. The platform aggregates capacity from multiple data centers to provide a single point of access, enabling rapid scaling of compute resources as demand fluctuates. Pricing is positioned competitively to lower the total cost of ownership for AI workloads, while the service includes automated provisioning and real-time usage monitoring to streamline operations.
Target Audience
The primary customers are AI startups, data‑science teams, and enterprise ML engineers who need flexible, high‑throughput GPU compute for model training, inference, or research without the overhead of managing physical hardware.
Features
- Instant provisioning of over 3,000 H200, B200, and B300 GPUs across multiple regions via a web portal and API
- Pay‑as‑you‑go billing model with no minimum usage or long‑term lock‑ins
- Auto‑scaling orchestration that adds or removes GPU nodes based on workload demand
- Unified dashboard for real‑time monitoring of GPU utilization, cost, and performance metrics
- Secure, isolated networking with VPC integration and role‑based access controls
- Compatibility with popular ML frameworks (TensorFlow, PyTorch, JAX) and container orchestration platforms (Kubernetes, Docker)
- SLA‑backed availability and redundancy across US and EU data centers