forloop.ai is an easy-to-use data pipeline and preparation tool, with intelligence.

With forloop.ai, a Data Scientist can:
- Independently set up data pipelines for models. Decreasing the need for DevOps and Data Engineers.
- Save time in the pre-model steps (getting the data ready). This often takes 80% of Data Scientists time. Based on current pilots, we estimate that we decrease that time by 30-40%.
- Drive business forward with 2x more time for ML creation. By decreasing time in pre-model steps, time is released for the creative aspects - modelling.


The solution consists of two central pieces:
- Pipeline: forloop.ai allows you, in a no-code environment, to draw a connection between a data source (let's say a data warehouse/lake) and where you host your model. In this tool, you apply transformations with drag and drop modules, and thus you can
continuously collect, combine and clean the data. In order to ensure a smooth transition between the current data scientist workflow, it ...
forloop.ai is an easy-to-use data pipeline and preparation tool, with intelligence.

With forloop.ai, a Data Scientist can:
- Independently set up data pipelines for models. Decreasing the need for DevOps and Data Engineers.
- Save time in the pre-model steps (getting the data ready). This often takes 80% of Data Scientists time. Based on current pilots, we estimate that we decrease that time by 30-40%.
- Drive business forward with 2x more time for ML creation. By decreasing time in pre-model steps, time is released for the creative aspects - modelling.


The solution consists of two central pieces:
- Pipeline: forloop.ai allows you, in a no-code environment, to draw a connection between a data source (let's say a data warehouse/lake) and where you host your model. In this tool, you apply transformations with drag and drop modules, and thus you can
continuously collect, combine and clean the data. In order to ensure a smooth transition between the current data scientist workflow, it is also
integrated with Python and Jupyter Notebooks.

- Built-in intelligence: By inserting data, forloop.ai learns from its structures, the behaviour (actions made on the data), and the
user's high-level objectives (defined by the user). By analysing these three points, it gives clues on what the next-best-action is and prompts the user a recommendation. By measuring the success rate of recommendations - it improves over time.
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Employees

Sebastian Berg
Admin
Sebastian Berg CEO Ex co-founder at LocalSound, an early employee at BotSupply (Enterprise AI software). MSc. Business & Data Science from CBS.