data infrastructure

In the first step Data Engineering / Processing stands for development and preparation of high volume and heterogeneous data sources. The very basic step to develop AI.


Tech: DWH, ETL, BI, Airflow, Spark, Hadoop

data visualization

We visualize data and insights. We inform employees in customer companies about the KPIs and create the basis for company decisions.


Tech: Tableau, Google Data Studio, mathplotlib, D3.js or Cytoscape

data analytics

We create reliable statements for the future. The identification and prevention of data distortions in samples and the entire data situation is required for training and development of AI modells.


Tech: Python, Mathematica, SPSS

machine learning

Gaining new insights with developed artificial intelligence based on previous qualified data. The result coukd be the core of new business models (or extension of existing ones) with NLP.

Tech: SciKit-Learn, Tensor-Flow, Space, Yolo or Prophet

© 2019 by Silpion AI Lab GmbH