Use Cases

E-Commerce

Cobalt’s TDA foundations give it a deep ability to analyze, compare and improve vector search embedding models for e-commerce applications.

This blog post describes our collaboration with Marqo to create an industry leading ecommerce solution that enhances embedding model fine-tuning.

Example Notebooks

E-Commerce Embedding Model Comparison

This shows how to apply Cobalt’s model comparison table to choose the best embedding model for your e-commerce vector database. Cobalt intelligently clusters together users’ product search queries into valuable and interpretable categories on which to compare different models.

E-Commerce Embedding Model Comparison (Fine-Tuning)

Similar to the above, but focused on tradeoffs from fine-tuning. The two models are a base E5 model from Hugging Face, and its fine-tuned version from using Marqo’s Marqtune platform to fine-tune. Cobalt reveals performance tradeoffs from fine-tuning through the model comparison table. Read more about our Marqtune integration here.