Off-the-shelf models know a lot about the world and little about your business. We train and fine-tune models on your own data, so they predict, sort and write the way your team needs. Before anyone relies on them, we test them on real cases.
How we work
01
Check the data
We look at what data you have, how clean it is and whether it can answer the question. Sometimes the honest answer is that you do not need a model.
02
Train and compare
We start with a simple baseline, then train or fine-tune and compare the results on cases the model has never seen.
03
Ship and watch
The model runs behind an API with monitoring, so we see when its accuracy drops and retrain it in time.
Built with PyTorch, TensorFlow, scikit-learn, Hugging Face, LoRA, OpenAI, Anthropic