We are very happy to enable DuckDuckGoose and their customers to fight the potential negative effects of AI. While AI can do much good, there is a negative side too. While we are working on solutions to enable responsible AI, such as explainability methods and ML auditing, a client like DuckDuckGoose is perfectly in line with our goals and ambitions.
The place to host and manage your data science models.
UbiOps is a fully-managed deployment and serving platform for ML & AI algorithms and data processing code. Easily create live, scalable prediction engines you can use from anywhere.
1. Create a deployment in UbiOps
Use our WebApp or CLI to define a deployment
Give your deployment a name, tell UbiOps what inputs and outputs your code expects (files, structured data, …) and how it should scale.
2. Upload or push your code
Package your Python or R code and deploy it to UbiOps.
Add a request function that UbiOps can recognize, and place it together with your requirements and necessary files in a single folder. This is your deployment package you push to UbiOps with our CLI or upload in our UI.
3. Ready to process data!
Your algorithm is now a live web service with its own API.
You can now make requests directly to the model API or by using our WebApp, client libraries and request scheduling tools. Connecting to data sources or integrating your deployment in your own website, dashboard or other application is easy.
UbiOps enables you to go quickly and easy from code to live application.
Check out these smart applications running on UbiOps!
Advanced analytics for Sustainable Buildings
BAM Building Analytics team knows that setting up a data science serving and operations backend is time-consuming. Rather than spending hours per week on managing Docker instances, cloud infrastructure and Kubernetes, they prefer to spend their time on experimenting and developing models.
With UbiOps, they can deploy immediately.
”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 MijleData Scientist at BAM Energy Systems
Online DeepFake detection
DeepDetector software helps professionals in supporting the decision process by providing statistics and in-depth analysis of the footage.
”By collaborating with UbiOps we can efficiently serve our machine learning models on their platform. UbiOps works like a charm and is a joy to work with for any data scientist.
Joris MollingaCo-founder at DuckDuckGoose
Trusted by hundreds of data scientists around the world!
“What I most appreciate are the fast response times and user-friendly UI. Have a new database, schema or storage platform? Just add a connector to the pipelines.”
Enrique GutierrezData scientist at ASSET Rail
“Examples provided are easy to follow and very practical. With documentation, it is possible to use UbiOps without getting any information up front.”
Stephanie LuikData Engineer at BAM
“By collaborating with UbiOps we can efficiently serve our machine learning models on their platform. UbiOps allows us to reach a larger audience in a very efficient way.”
Joris MollingaCo-founder at DuckDuckGoose
Let's start running your code live. And for free.
Get to market fast with UbiOps and create value from your data science initiatives.
Create accountStart for Free, pay as you grow. 100% flexible, upon your needs.
FreeAlways free
€ 0.00
Per Month- Hosted by us.
- Max. 1 user, 1 project, 5 deployment versions
- 100 GBh compute per month
- More than enough to run your first models
- Core functionality
- Best effort support
Pay as you grow
€ 49
Per Month- Hosted by us. For individuals and teams. Pay for the users and compute you need.
- Unlimited projects and deployment versions
- 1000 GBh compute per month
- Extra compute for €0,05 per GBh per month
- Core functionality, including team features
- Upgrade easily from your UbiOps account
Enterprises
€ upon request
Per Year- For small, medium-sized and large enterprises. Hosted by us (SaaS), or installed on your clusters (OnPremise). Tailored to your wishes.
- Can be installed on Google Cloud Platform (GCP), Amazon Web Services (AWS) and Microsoft Azure. As well as on other infrastructure supporting Kubernetes.
- Contact sales
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