About Us
Data is still the missing piece
of companies AI strategy
Models are what they eat.
Models are a reflection of the data used to train them. Yet, the process of determining which data are vital is a daunting and challenging task. To date, this process has been manual. Companies send their data to a data labeling service that recruits subject-matter experts to label data by hand. Then, the companies must explore large volumes of labeled data and select what data to use for training. Automating this process is difficult — but it represents the most critical challenge to AI performance to date.
We faced the pains of curating data and developing models ourselves at companies like Delivery Hero, Rocket Internet, Yelp, Autodesk and in Research Institutes across the world.
We spent – month-long data annotation campaigns, followed by weeks of iterating on a model. A turnaround of a new idea required us months and a team of Machine Learning experts & annotators.
With the advent of LLMs and new research in knowledge distillation and model compression, we decided to bring the benefits of the state of the art methods to non-experts, so they can also start building their applications with SLMs with ease.
We are experts in AutoML, NLP and building scalable data products, so you don’t have to
Tameesh and Matteo, founders of Claro