Cake for Dataset Creation

High-quality data is your competitive edge

Models are only as good as the data they’re trained on, and most teams spend a disproportionate amount of time collecting, labeling, and transforming datasets. Whether you’re building supervised models or fine-tuning a foundation model, dataset creation is where quality starts.

Cake integrates open-source tools like Label Studio, Hugging Face, and Feast into a unified platform. Annotate raw data, generate synthetic samples, track feature versions, and manage labeling workflows with reproducibility and orchestration built in.

Because Cake is cloud agnostic, you’re never locked into a single storage backend or labeling workflow. Your data workflows remain portable, reproducible, and easy to integrate with downstream training and evaluation pipelines.

Key benefits

• Speed up iteration: Reuse workflows across training, fine-tuning, and evaluation pipelines.
  
  

• Build on trusted tools: Label, structure, and generate data using open-source frameworks like Hugging Face and Label Studio.
  
  

• Keep it compliant and portable: Ensure your datasets are secure, reproducible, and cloud agnostic. Comply with industry regulations like SOC2 and HIPAA.