Run your AI workloads at scale
Powerful AI model serving and orchestration with unmatched simplicity, speed and scale.
Get to know UbiOps
Launch scalable AI products in
a fraction of the time
UbiOps is an AI infrastructure platform to help teams to quickly run their AI & ML workloads as reliable and secure microservices, without upending their existing workflows.
Integrate UbiOps seamlessly into your data science workbench, and avoid the burden of setting up and managing expensive cloud or on-premise infrastructure.
Whether you are a start-up looking to launch an AI product, or a data science team at a large organization. UbiOps will be there for you as a reliable backbone for any AI or ML service.
Built-in MLOps capabilities to take your AI products to the next level
The fastest route to production-grade ML / AI workloads
Deploy models and functions up to 10X faster, from fine-tuned LLMs to computer vision models. Train and deploy any AI or machine learning models in a turn-key production environment with scalable inference endpoints.
Deploy LLMs in your own private environment
With UbiOps you can easily deploy off-the-shelf foundation models like LLMs and Stable Diffusion in your private UbiOps projects and even run them on your own infrastructure with UbiOps’ hybrid cloud and on-premise orchestration capabilities.
Out of the box AI infrastructure
Run your first job in minutes with zero MLOps or DevOps experience. Manage countless AI workloads simultaneously from a single control plane. Integrate easily with the tools you know, like PyTorch and TensorFlow. Built-in version control, simple rollback, monitoring, logging, and more.
Secure and compliant by design
UbiOps provides robust security features such as end-to-end encryption, secure data storage, and access controls. Facilitate business compliance with regulations such as GDPR and SOC 2, and use off-the-shelf generative models without worrying about data privacy.
UbiOps is NVIDIA AI Enterprise partner
"Becoming an NVIDIA AI Enterprise partner is a big step on our mission to provide data science & AI teams with the best infrastructure and capabilities for running and managing their AI workloads to build production ready AI services."
Optimize compute with rapid adaptive scaling
Scale your AI workloads dynamically with usage without paying for idle time. Accelerate model training and inference with instant on-demand access to powerful GPUs enhanced with serverless, multi-cloud workload distribution.
Easily handle peak loads for notoriously compute-intensive LLMs, CV, and generative models with automatic scaling and zero-scaling.
Multiple compute environments, one interface
UbiOps supports hybrid and multi-cloud workload orchestration.
Deploy models on your own infrastructure or private cloud, where data and models never leave your environment. Or scale out to hybrid and multi-cloud environments to optimize for costs, compliance and guaranteed compute resources.
Build modular applications
Improve the efficiency and scalability of your applications with Pipelines: UbiOps’ unique workflow management system. Re-use and combine multiple deployments (or sub-pipelines) into a workflow with its own unique API. Customize inputs for each object in the pipeline by splitting and reassembling data.
Add Operators for ultra-fast parallel processing, conditional logic, data transformations and alerts.
Customer Success Stories: real voices, real results
The National Cyber Security Center, innovates with UbiOps towards a digitally secure Netherlands
Diving into the world of coral reef conservation: how Reef Support trains AI with UbiOps
For the next generation of AI and ML builders.
Rapid, on-demand scaling of AI workloads on GPUs without running into complex cloud infrastructure, high costs, or scaling issues.
Building instead of maintaining
Setting up the right infrastructure to run, manage and scale AI workloads can be a huge investment. UbiOps offers you a turn-key solution, so you can focus on developing AI products instead of maintaining infrastructure.
Built for all data scientists
UbiOps is built to let any data scientist or team turn data science models into live, scalable applications. Easily create analytics services and workflows you can use from anywhere.
Train and serve any AI/ML model
Run any workload as a scalable service with its own API, or as part of a pipeline with multiple services. You can use UbiOps for both AI model training as well as serving & orchestration.
“The on demand offering of UbiOps ensures that there’s GPU availability, with the option to scale very rapidly. Also, with UbiOps’ scale-to-zero functionality we don’t need to pay for GPU resources if the application is not being used, e.g., off-season.”
Dr. Alexander Roth
Head of Engineering - Digital Crop Protection at Bayer
”I am a self-taught Data Scientist and have no MLOps knowledge. UbiOps allowed me to reduce a 4-hour process to 15 minutes thanks to its intuitive pipeline construction interface and parallelization method. No worries, the software is easy to pick up.”
Adrien Raynal
CEO Emersio
“Thanks to UbiOps, it will bevery easy and quick for us to scale up. Because of the fact that everything happens in the cloud, it doesn’t matter where the greenhouse is located. We could have customers all over the world.”
Wilmar van Ommeren
Product Innovator Ridder
”Using UbiOps, our team is able to orchestrate all processing steps and data flows seamlessly so we could start using our models while minimizing DevOps costs.”
Hervé Huisman
Founder & CEO at Gradyent
”UbiOps helped us to deploy our product to a production environment in a scalable but cost-effective manner. Their platform works like a charm and is a joy to work with for any data scientist.”
Joris Mollinga
Co-founder at DuckDuckGoose
”UbiOps enables us to develop, deploy and operate any type of data science code, without having to worry about the IT infrastructure. Even when we continue growing in size and amount of data science applications.”
Pieter van der Mijle
Data Scientist at BAM Energy
What our clients say about us
Integrate UbiOps seamlessly into your data science workbench, and avoid the burden of setting up and managing expensive cloud infrastructure.
