Data and feature strategy
Location page: Berlin
Custom ML Development for Companies Berlin
Development, training and integration of machine learning models for prediction, classification and intelligent product features.
Berlin is strongly shaped by SaaS, venture-backed startups and digitally driven service models.
Request ML projectML from data to deployment
I build ML pipelines from data preparation and feature engineering to model training, evaluation and production deployment. Example implementations include an AI Real Voice TTS for Voicfy based on a diffusion model and a news-gathering trading system that performs stock-level fundamental analysis.
Model training, evaluation and iteration including diffusion models for audio/TTS
Deployment, monitoring and MLOps setup for production ML and analytics systems
Berlin market context
Industry focus
- - SaaS & B2B software
- - Creator economy
- - Digital services
Local leverage points
- - Fast pilot cycles
- - Multilingual teams
- - Scale after PMF
FAQ
When do you need a custom ML model?
When off-the-shelf models do not provide the required accuracy, latency or domain fit for your use case.
Can a model be integrated into existing systems?
Yes. Integration is possible via APIs, batch pipelines or direct product features, including monitoring in production.
Do you have practical ML examples from your work?
Yes. This includes an AI Real Voice TTS for Voicfy based on a diffusion model and a news-gathering trading platform with per-stock fundamental analysis.
How fast can a pilot start in Berlin?
Usually within 2-4 weeks after discovery and scope approval.
Do you work with distributed Berlin product teams?
Yes, delivery is designed for hybrid and remote team structures.
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Start your project in Berlin
Share your goal, timeline and budget for Berlin. You will get a clear recommendation for the next step.