Horizon Compute offers a cloud‑native platform that gives AI developers and ML engineers instant, on‑demand access to NVIDIA A100, H100, and A40 GPUs through a web console, REST API, Terraform modules, and a native Kubernetes operator. The service provides pay‑as‑you‑go and reserved pricing, VPC‑isolated security, integrated monitoring, and 24/7 technical support to enable scalable training and inference workloads.
Funding
Funding not disclosed
Founders
Product
Problem
AI teams often face long provisioning times, high capital costs, and limited scalability when accessing high‑performance NVIDIA GPUs for model training and inference. On‑premise GPU clusters can become underutilized or insufficient for burst workloads, leading to delayed experiments and increased time‑to‑market. Smaller firms and research groups lack the budget and expertise to maintain and upgrade specialized hardware.
Solution
Horizon Compute delivers a cloud‑native GPU infrastructure that provides instant access to the latest NVIDIA GPUs (e.g., A100, H100, A40) via on‑demand or reserved clusters. Users can spin up GPU instances through a web console, REST API, or Terraform provider, enabling seamless integration with existing CI/CD pipelines. The platform supports containerized workloads with Docker and Kubernetes operators, allowing automatic scaling based on job queue length or custom metrics. Billing is granular, measured per GPU‑hour, while reserved capacity offers predictable pricing for sustained projects. All traffic is encrypted and isolated within VPCs, and the service includes built‑in monitoring, logging, and role‑based access control. Research‑led support assists customers in optimizing GPU utilization and troubleshooting performance bottlenecks.
Target Audience
The primary customers are AI developers, data‑science teams, and ML engineers in startups, enterprises, and research institutions that require high‑throughput training or low‑latency inference. It also serves DevOps teams that need to embed GPU compute into automated pipelines and CI/CD systems.
Features
- Access to NVIDIA A100, H100, and A40 GPUs with up to 80 GB of VRAM per instance
- On‑demand provisioning via web UI, CLI, REST API, and Terraform modules for IaC workflows
- Native Kubernetes operator and Helm chart for automated GPU node scaling and pod scheduling
- Pay‑as‑you‑go pricing (per GPU‑hour) and reserved capacity contracts with volume discounts
- Secure VPC isolation, TLS encryption, and IAM‑based role‑based access control (RBAC)
- Integrated Prometheus‑compatible metrics, Grafana dashboards, and log aggregation for performance monitoring
- Pre‑installed deep‑learning frameworks (TensorFlow, PyTorch, JAX) and CUDA/cuDNN libraries, with one‑click environment updates
- 24/7 technical support staffed by GPU‑performance engineers for optimization guidance