• Skip to main content

Codesymmetric

.NET Entwicklung und Beratung in München

  • Home
  • .NET development
  • Case studies
  • Contact
  • EnglishEnglish
    • DeutschDeutsch
    • EnglishEnglish

Machine learning engineering

We design and implement custom-tailored AI systems for your business and your industry.


Integration with existing systems

AI systems are most often developed in connection to existing data sources. These could, for example, be ERP systems, industrial automation systems, databases with customer transactions and other data sets, which make up the data foundation for the AI. As part of the data importing process, we also handle import automation and data cleansing.

Our process

Our AI development process differs from project to project, but it generally follows the following procedural model that consists of four phases (see image):

  1. Problem analysis and definition
  2. Data collection
  3. Modelling
  4. Deployment and operation

We handle the entire process but are also happy to take over partial steps in collaboration with your IT teams.

Vorgehensmodell für KI-Entwicklung, Quelle: Google Inc.
PROCEDURAL MODEL FOR AI DEVELOPMENT, SOURCE: GOOGLE INC. 

Technologies

  • Deep Learning — TensorFlow, Keras
  • Classical CPU-based ML — Sklearn
  • Automation of integration and deployment — Kubeflow Pipelines
  • Defence — IBM Adversarial Robustness 360 Toolbox
  • Training — in-house GPU Hardware or cloud 
  • Integration with big data
  • Legal Disclosure
  • Careers
  • Case studies
  • About us
  • Contact

Copyright © 2025 Codesymmetric GmbH, München