fast and effortless ladder

Rove Analytics support of large-scale competition in addition to AWS, Microsoft Azure, Google Cloud Platform & on-premises hardware (e.g. OpenStack). Just click on a button and launch your code in the Dockers containers on your chosen hardware.

automate version control

Ensure regulatory compliance without adding work. Rove Analytics Inc. automatically tracks all your experiments, with a clear picture of how each model was formed, from data to algorithm to parameters & statistics. Repeat previous experiences at any time.

pipeline management

Do not worry about the environments, configurations or closing of the servers when your training is complete. Streamlined and extensible Rove Analytics API allows you to focus on testing and controlling your models!

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to store and view each experience

Feed backs

We believe that effective version control is key to achieve reproducibility, regulatory compliance, audit trail and efficient results. From now on, or 10 years from now, you will be able to select a deployed model and clearly trace its hyperparameters,
training data, script version, associated costs, siblings models and even the team members who participate in its training.

Visualize and Monitor

You will see everything in real time as your training progresses, you will no longer be stuck manually running models and keeping track of CSV files. Get visual feedback on everything from the performance of a single model to a convergence of several parallel hyperparametric scans. See how your parameter scans progress while comparing competing models by precision, depth, or any custom parameter. You can also view custom settings in stdout and view them graphically in Rove Analytics the web-based interface.

integrating everywhere

Rove Analytics works with any runtime you have and executes any machine learning code you write. Unlike other deep learning tools, we do not link you to a single vendor (not even ourselves – even the configuration format is open source).

standardized workflow

Rove Analytics provides you with the same industry-leading tools and best practices that power plants like Uber, Netflix, AirBnB and Facebook use to manage their internal machine learning pipelines.
Rove Analytics streamlined learning chain ensures the integration of steps, regardless of who wrote the code or what language or framework was used. Generate images with Unity, convert to custom C-code, form with TensorFlow as Python, deploy to a Kubernetes cluster. Everything works in the box!

Complex automation pipeline data

Everything in Rove Analytics is built API-first for easy integration of your ML pipeline into your existing software pipeline, for example through Jenkins or any other platform for continuous integration.



Rove Analytics allows you to scale vertically and horizontally to do Distributed Learning and hyperparametric scans parallel to the speed of light (in an ethernet cable). Run your model in parallel on a hundred GPUs or tell Rove Analytics Inc. to go through different hyperparameters to find the best model for your data in parallel on tens of TPUs. Rove Analytics Inc. is designed to find and optimize your model for big data and huge models that scale with you, as you move from data mining to production.


Form your models in the cloud or on your own farm-server with the click of a button, the call of an API, or a clone-liner. Rove Analytics Inc. allows you to use the right amount of processing units-maximizing your results while saving time and money.
Give your science team total transparency about how models have been formed throughout their history until all team member’s projects are fulfilled.


Protect your business and customer data by hosting all your assets in your own cloud or on-site data storage environment. Rove Analytics supports any storage platforms from Amazon S3, Azure Blob Storage, an HTTP endpoint or a directory on your intranet.