We have a library with about 100 algorithms which you can choose from or by default we automatically choose based on your objective.
Majority of them are open source models we've forked and improved. Just as an example, we integrated in gSASRec last week: https://github.com/asash/gSASRec-pytorch, and added a couple of improvements on scale and the ability use language and image features. We use LLMs for the encoding of unstructured data, and we host these our self, although OpenAI and Gemini are used for error message parsing and intelligent type inference, things not on the real-time path.
Majority of them are open source models we've forked and improved. Just as an example, we integrated in gSASRec last week: https://github.com/asash/gSASRec-pytorch, and added a couple of improvements on scale and the ability use language and image features. We use LLMs for the encoding of unstructured data, and we host these our self, although OpenAI and Gemini are used for error message parsing and intelligent type inference, things not on the real-time path.
More info here: https://docs.shaped.ai/docs/overview/model-library