Machine learning and data engineering Put your data to work every day.
Orders in your ERP, readings in your control system, documents in your inbox. We connect your sources and collect what is missing. Then we develop forecasts and analyses for your task and bring the results straight into your software.
Use your data for a concrete task.
Start with a task that takes up your team’s time today. We build the dataset and the analysis it needs.
What we build with you
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Forecast demand and utilisation
We develop forecasts from historical patterns to help you plan staffing, materials and capacity.
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Spot unusual activity
We flag unusual readings, transactions or process patterns with the context your team needs to investigate.
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Extract information from documents
We classify documents, extract details and link each result to its source.
Collect data
We connect databases, APIs and exports, extract data from documents and set up new logging for measurements and processes. We add public data through APIs and web sources with agreed usage rights.
We collect the fields you need at the right time intervals. For supervised learning, we label examples and check the labels with your subject experts.
New data is ready for analysis. Your team can see which sources, fields and time periods it covers.
Connect and prepare data
We build repeatable imports, align IDs, timestamps and units, and remove duplicate records. Quality checks show missing values and incomplete data feeds.
Every record keeps its source reference. A documented schema describes the fields, formats and processing steps.
Your team works from one shared dataset and can see when a data feed is missing.
Develop and evaluate models
We develop models for forecasting, classification and anomaly detection. We compare each model with a simple baseline, such as last year’s value or a fixed rule. That shows you whether the extra effort is worthwhile.
We test with data that was not used during development. We evaluate forecasts on later time periods, using only information available at the time of the decision. We measure errors and uncertainty, including for individual sites or groups.
You can compare the accuracy of each approach and decide which fits your task.
Bring results into your software
We deliver data and model results to your software through APIs. Access controls protect the data, and model versions make changes traceable. We route cases with high uncertainty for expert review.
We set up quality checks and alerts for data problems, and show your team how to run and develop the application.
Your team uses the results directly in its familiar workflow.
Let’s start with your task.
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Talk through the task
Tell us what your team gathers, calculates or checks today. We discuss what result would make that work easier.
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Work with the data
Show us a schema or an anonymised example. We test initial approaches on a data sample and propose an implementation with an estimate of effort and cost.
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Put the approach into practice
We develop the chosen approach, connect it to your software and test it with the people who will use it.
See how we analyse data.
In our Polymarket study, we group trading behaviour using fixed rules and compare the patterns. Read the method and results in the study.
Read the studyHappy to work with your team.
You know your business; we handle the technical work. Your IT and subject experts work directly with us, Elias and Justus, from the first data sample to the running application.
Tell us what your team wants to achieve.
Write a few sentences about your task. We’ll discuss the right starting point with you.