Collect external data and automate it with just a few clicks is an easy-to-use no-code tool for building of processes continously feeding external data. 

It comes with built-in data preparation features and intelligent recommendations. Allowing you to get an information advantage and have data ready for analytics on a continous basis, with ease. 

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No-code tool to make teams more productive

Everyone is talking about AI and ML. Optimizing this, automating that. However, 87% of these initiatives never reach production.

Most often, it's not the models itself that is the roadblock. Rather all the work with the data that is needed. Meaning, have it collected, prepared and ready. Which in many cases, takes 80% of a data scientists time.

To solve this, and to have data running smoothly, a full team is needed. Making it a very resource-heavy operation with slow iterations. Leaving a lot of companies behind to leverage ML. 

Product overview not tight edges

How It Works

  • 1

    Set up your data processes in minutes

    Using our unique no-code platform, you can start building data processes simply by clicking and connecting the modules you need for data collection, cleaning, aggregation, or other transformations. Run all of these steps automatically with custom triggers to get results continuously at near real-time basis. This is especially powerful whenever data sources get quickly old and need to be refreshed very often.
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  • 2

    Get productive with Augmented Intelligence platform comes with Augmented Intelligence, an AI system recommending the best steps in process building based on user's objective and given data sources. To make sure the user is happy with the recommendations, it is possible to correct the specifications repeatedly in a feedback loop, and thus iteratively getting to the end result. No matter whether you want to automatically do webscraping, cleaning, or transforming tasks, with manual coding becomes a history.
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    Boost your speed with no-code while keeping your flexibility with code view platform comes with a mapping between code and no-code which helps the user to export created pipelines to Python code or import code which gets automatically mapped to platform. This way processes get created much faster in a no-code way while user can still tinker with the code details under the hood. It also enables the user to use open source packages and keep versioning projects in user's preferred way.
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With, the production time was cut by 45% to create the foundation of our dynamic pricing model. We now have continuous clean data, that is auto transformed, in a stable pipeline. Allowing us to create models way faster. 

Jaime, Co-founder / CTO

With, we have been able to collect and combine external data to have it ready for modelling. Allowing us to create recommendation models with ease with no need to hire data engineers. Enable us to increase revenue by 15%

Alan, Co-founder / CEO

An easy to use data pipeline and preparation tool, with intelligence.

Removing the data bottlenecks for ML models and decisions, by enhancing the data scientist

  • Webscraping

    Gather your data from the web sources and automate the use of your computer with RPA

    In some data tasks it happens, one would like to add some data that need to be extracted from external web sources or some old legacy apps which don't have API. For that reason, comes with a set of Webscraping and RPA (Robotic Process Automation) tools to ensure you don't have to switch to other tools to gather the data you need for your work. 

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    Set up, orchestrate and manage ML workflows at scale helps you build, deploy and manage data pipelines for your ML models - in minutes instead of weeks. No data engineers needed. A graphical UI to oversee the pipeline, with code interface for version control and easier editing.

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    Sweep through the data prep

    Data preparation, with AI-assistance. By inserting data, it learns from its structures, the user actions and the user high level objectives (e.g for the training of a dynamic pricing model). To overtime, automate more and more of the mundane data tasks, ensure data quality and enhance the data scientist.

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    Proactive quality assurance

    Ever had a new batch of data coming in that is formatted differently and make things crash? proactively monitors the quality of incoming data. If it deviates from the threshold - you get alerted. 

Now launching

We're working with forward-thinking data teams to go from raw data to ML models in production. If you are interested in a hands-on partnership, we’d love to get in touch.  

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