Problem and data assessment
Define the prediction or classification task, review the available data, and agree the baseline and evaluation criteria.
AI & automation
Machine learning features built around your data
Machine learning for features that need to classify, predict, or recommend. We work through data preparation, model experimentation, evaluation, and integration into your product.
Discuss a machine learning feature
How we approach this work
A useful model needs a defined product goal and suitable data. We start by examining the task, available examples, and a practical baseline. Model work then follows a repeatable process so the team can compare results and understand the tradeoffs before integrating the feature.
What we work on
Training and evaluation
Prepare data consistently, separate training and evaluation, and run reproducible experiments to compare suitable approaches.
Integration and monitoring
Connect the selected model to a service endpoint or batch workflow, then monitor the behavior and data changes that matter to the feature.
Explore the Use Cases
Illustrative scenarios with proposed tools and implementation notes.
For custom development
Tell us what the feature should predict or recommend, which data is available, and how the result will be used in your product.