Train, Serve, and Manage AI and ML Models On Any Infrastructure

10x faster Go-To-Market

Up to 80% lower TCO

Pipelines UbiOps

Trusted by teams building the next generation of AI products

AI workload orchestration without Kubernetes or Slurm

Run and autoscale workloads directly on bare metal, virtual machines or interact with IaaS API.

Cost-effective model inference and training

Deploy machine learning models as scalable inference APIs and offload long-running training jobs to powerful cloud hardware, all the while only paying for the time your models are active.

Save up to 85% on AI infrastructure costs.

For any AI application

 

Deploy off the shelf models or run custom data science code. UbiOps serves your Python or R code and instantly scales in the cloud, for real-time serverless inference or long-running jobs.

Create single services as well as large modular workflows. Choose between efficient CPU or accelerated GPU instances.

 

On any infrastructure

 

Run workloads in our fully managed platform, across hybrid cloud environments or on-premise. All from a single control plane, without compromising security or privacy.

 

See the value in action

Enjoy benefits backed by real-world results

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Lower costs

Why UbiOps?

Built for data science teams

UbiOps automatically turns your code into a service with a secure API and takes care of load balancing, automatic scaling, monitoring and security.

Streamline your MLOps and reduce costs

Save on DevOps investment and manage all your models in one place, complete with version control, logging, auditing and monitoring.

Automate your workflow through our easy-to-use browser interface, your preferred IDE, or a terminal.

Keep track of everything in one place

View metrics on usage and performance. Check if there are any issues with your deployments. Set alerts and notifications. 

Get insights into everything that’s going on with extensive logging.

Deploy in no time

 

Don’t worry about Kubernetes, Docker images, uptime, scaling, or security. 

Focus on developing your models and let UbiOps take care of the rest.

From training and fine-tuning to deployment and serving, launch production-grade AI services in 10 days, not 10 months.

Deploy and scale anywhere with superior security

UbiOps will take care of orchestration in the background based on your needs​

Deploy on our SaaS solution, hybrid cloud or on-premise

Choose where your AI workloads run. Attach multiple compute environments to the UbiOps control plane. Enhance your local infrastructure with the power of hybrid cloud and optimize for costs and compliance.

Auto-scale with on-demand compute

Choose the compute instances to suit your model and gain access to both efficient CPU and accelerated GPU hardware that scales automatically based on incoming data to and from zero. Only pay when your deployments are running. Don’t pay for inactive models.

Get access to the right hardware on the multi-cloud UbiOps platform

Avoid GPU shortages or local hardware limitations. UbiOps leverages multiple compute environments, offering broad GPU availability and a range of different instances to match your needs.

Improve security, privacy, and compliance

Control how data is processed, where it is processed and whether data is stored on the platform. Your data, your rules.

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.

Create and orchestrate workflows

Build modular applications by re-using and combining multiple deployments in a workflow.

Improve the efficiency and scalability of your ML apps

Each workflow gets its own unique API and each object in a workflow is an isolated service that scales independently.

Construct your own data pipeline

 

Funnel data through all your deployments or bypass deployments. Embed sub-pipelines or add conditional logic to data flows.  Simply drag and drop.

Collaborate simply and effectively

 

Import or export pipelines directly and share them with your colleagues or other users.

Save time and optimize your computing

 

Use pre-built operators to help guide and modify data running through your workflows. Customize inputs for each deployment by splitting and reassembling data.

Train your ML models in the cloud

Offload long-running workloads on powerful cloud hardware

Train and deploy your AI faster

Upgrade your training speeds with on-demand access to top of the line GPUs. Save time by standardizing and easily re-using code environments for both training and inference.

Achieve better machine learning performance

Customize your own performance metrics and compare between different training runs as well as across experiments. Find the model that works best for you.

Integrate training and inference

Train, re-train, and deploy into production – all within the same interface.

UbiOps integrates seamlessly with the data scientist’s toolkit

Turn your AI & ML models into powerful services with UbiOps