Deep Lake AI Knowledge Agent conducts Deep Research on your data, no matter its modality, location, or size. Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) stored anywhere, to AI. Over time, it learns from your queries, tailoring the results to your work! Deep Lake is used by Fortune 500 companies like Bayer, Matterport, and others.
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Here are few things that I really liked in my first experiments.
1) Being able to use lots of public data sets before porting my own. Gave use good idea what the usability would be like so it was really helpful.
2) Found the onboard for data access quiet helpful, lots of things were present that were really on point, e.g. CORS configs.
3) Really liked step by step presentation of things before final output would be generated. Would want to see more control there.
Example, when doing a search it allows to see "Generating TQL", which is great, now I want to see what would happen if I were to change TQL itself. Could I see side by side data? Could I see performance metrics. Not all queries are equal in backend side so may be I want to speed things up or help things get to better results.
I can see that the platform does have the ingredients so looking to explore further and give more updates here.