UbiOps is developed for teams that are looking for an easy, cost-efficient, and scalable way to run and manage AI workloads as live services in the cloud.
Trusted by the world’s premier technology and solution providers
From code to scalable services
From training to inferencing jobs, UbiOps helps AI/ML researchers and data scientists to very quickly turn their data science workloads into robust and secure microservices.
This without requiring knowledge to set up Cloud infrastructure and DevOps practices.
Long-running
video processing jobs
UbiOps helps Royal BAM to run computer vision models that can process massive amounts of image and LiDAR data.
Real-time
computer vision
UbiOps helps Bayer Crop Science to scale with computer vision workloads on-demand on image and video data across GPUs rapidly and easily.
Large scale
time-series analysis
UbiOps helps Gradyent to run real-time time series to operate real-time critical energy networks. Large-scale geographic, sensor and weather data are used to feed AI to get insights into the real-time performance of physical networks.
Pattern recognition
on large datasets
UbiOps helps NCSC to run business logic and machine learning on large datasets to detect digital threats sooner and more efficiently. UbiOps fits within the security framework that the NCSC wishes to comply with.
Manage and scale AI workloads on GPU infrastructure
On-demand orchestrating and scaling AI workloads on GPUs without running into availability issues, high costs, or complex DevOps is one of the biggest challenges of existing solutions.
Optimise GPU costs
Adapt to your changing workloads on-demand.
Scale up and down across GPUs rapidly.
Easy to use
Run, manage and scale AI workloads on GPU/CPU infrastructure with an easy-to-use interface.
Without the need to rely on DevOps and IT knowledge.
