Fovus is an AI-powered serverless high-performance computing (HPC) platform that automates the optimization of cloud HPC strategies, enabling enterprises to efficiently deploy and scale workloads while minimizing runtime and costs. By eliminating the complexities of cloud integration and management, Fovus enhances productivity and accelerates time-to-insight, achieving cost reductions of 2-7 times through intelligent resource allocation.
Funding
$4.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises face significant challenges in managing high-performance computing (HPC) workloads in the cloud due to the complexity of cloud integration, diverse cloud offerings, and rapidly evolving infrastructure. Optimizing HPC strategies for speed and cost requires specialized expertise and constant adaptation, diverting resources from core innovation activities.
Solution
Fovus provides an AI-powered, serverless HPC platform that automates the optimization of cloud HPC strategies, enabling enterprises to efficiently deploy and scale workloads while minimizing runtime and costs. The platform abstracts away the complexities of cloud logistics, auto-benchmarks workloads to determine optimal strategies, and dynamically scales resources based on workload requirements, license availability, and cloud pricing. Fovus continuously improves HPC strategies by auto-updating benchmarking data and adapting to evolving hardware technology and cloud infrastructure. By leveraging AI and automation, Fovus reduces cloud HPC costs and accelerates time-to-insight, allowing users to focus on innovation.
Target Audience
Fovus targets enterprises in industries such as manufacturing, biosciences, and computer-aided engineering (CAE) that require high-performance computing resources in the cloud.
Features
- Single-command deployment via CLI or web UI for easy workload launch
- Automated benchmarking to explore HPC strategy space and identify optimal configurations
- Dynamic scaling of license-required workloads based on license availability
- Efficient scaling across multiple cloud zones and regions for license-free workloads
- Intelligent leveraging of spot instances to reduce cloud HPC costs
- Continuous improvement of HPC strategies through automated benchmarking data updates
- AI-powered optimization that adapts to evolving hardware and cloud infrastructure