What is Embeddings?
What does 'Embeddings' mean?
An embedding model turns a passage into a vector so that text with a similar meaning lands near it, which is what makes retrieval by meaning possible at all. The practical differences are context length, how well the model handles the language and domain you work in, the vector size and the cost it adds to storage, and the token rate. Changing model later means re-encoding the whole archive, so this is a decision worth testing on your own content first.
List of software with Embeddings functionality
About the reviewer
Rajat Gupta is the founder of Spotsaas, where he has built software research covering 25,000+ products across CRM, HR, AI, and finance. He applies hands-on product research and a background in commerce and the CFA program to evaluate software through a business and ROI lens. His goal: help teams make software decisions they won't regret.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].