We are a team of 5 machine learning engineers from Berlin. We started in 2015, predicting user behavior for big websites. Now we manage more than 15 production AI systems in Web, Finance, Energy and Disease Diagnostics.
What Our Clients Say
“The team at Data Revenue is a pleasure to work with – open, curious, professional, and non-bureaucratic. They take an active role in every step of the process, and they think ahead. They went the extra mile for us, and we really trust them.”
Joern Hagenguth, Head of Relocation
Learn how to apply AI to your business. We guide your team through discovering the most promising AI use cases.
Get the AI solution you want. We prepare the data, select and tune the algorithm, validate the results, and then go live. Plus, we make sure your team knows how to get the most out of the results.
Tripling email revenue
ImmobilienScout24, the biggest real estate portal in Germany wanted to improve their email targeting.
We build a predictive targeting solution that improved revenue by 250% on average.
AI recommendations in 4 weeks
Ladder.io hand-picks growth tactics for young companies from a pool of more than 1.000 tactics — and they wanted to teach a machine to do the same.
In 4 weeks, we built an API that predicts the right tactic with 95% accuracy.
“It was a great project. Definitely a breath of fresh air compared to some other vendors we’ve worked with. Data Revenue is experienced, genuine, and they really know their stuff. We knew right away that we could trust them.” - Michael Taylor, Co-Founder & COO, Ladder Digital
Benchmarking an algorithm in 3 days
Billpay, a leading online payment provider with more than 10 million customers, wanted to know if they could improve their fraud detection.
We built a benchmark model with stronger, cutting-edge algorithms in less than a week.
Work with the best tools
Successful AI projects are nimble, extensible and use the best tools for the job. That’s why we value code quality (including tests and documentation) — we work with Python 3.5+, build models with scikit-learn, XGBoost and TensorFlow. And we run projects on single AWS EC2 instances with Dask and Luigi — deployed with Docker.