Our products
How we can help you with your machine learning needs
Our offer
We help businesses to get more out of their machine learning efforts by providing solutions that improve their process in 3 different ways:
Make your life easier
Supercharge the productivity of your engineers and scientists
When new machine learning processes are developed scientists and engineers spend time not only on choosing the right algorithm and dataset, but also to preprocess the data, evaluate the model and manage the computational resources manually. This involves setting up the computation infrastructure, deploying their code, starting the necessary processes and keeping track of intermediate artifacts. All these additional tasks slow down the development process, make it error-prone and have a negative impact on the motivation.
To improve the developer experience we are currently working on a set of libraries that can be easily integrated into python scripts and automate a lot of these tasks by providing the following features:
- Splitting python scripts into independent logical tasks that can be run individually
- Easy integration using decorators
- Support for running tasks with different python interpreters
- Asynchronous execution of tasks
- Automatic deployment and running on different computational platforms (local, cluster via SSH, etc.)
- Tracking of intermediate artifacts
- Reusable configuration
The first product is planned to be available in Q4 2021.
Optimize your costs
Understand how efficient your process is and discover optimization potential
Typically, machine learning processes are developed in multiple sequential steps. Unfortunately most of the time the process isn’t as straightforward as one would want it to be. During development issues come up that require changes to previous steps, so that one needs to go back and start over. Therefore, in reality the process looks more like this:
This can lead to multiple calculations of the same data and creating the same intermediate result over and over again.
Additionally, all those steps have different run-time behavior and a diverse set of computational requirements, even though they are often all run on the same computation platform.
Our solution keeps track of all individual tasks together with their input and output data. It collects profiling information about each task to give you insight about the efficiency of your whole process. This enables you to:
- Determine the computational cost of your model and its individual parts
- Avoid unnecessary re-computation of intermediate results
- Find hot-spots in your code that consume most of your resources
- Discover tasks that require more resources than they actually use
- Run tasks on the most cost-effective machines
Be compliant
Enforce regulation compliant data handling throughout the whole process
Often data that is being used in building machine learning models is subject to regulation that requires specific handling, especially if you use sensitive data from customers.
By integrating our tools you can keep track of the source of data throughout the whole process and make sure, the necessary mechanisms are in place to be compliant with every regulation that is relevant for you.
- Understand which data is used in your models
- Manage the life-cycle of your artifacts automatically
- Create automatic audit logs that show your compliance
- Define custom policies that are automatically applied to all your data
