Ant Wilson

Supabase Vector - The open source backend for AI applications

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Supabase Vector is an AI toolkit to power any AI application. - Store vector embeddings at scale, alongside your users data. - Works with any language, stack, or programming environment. - Example projects to get you started. - Start for free on our cloud.

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Brady Lewis🤖
Fantastic!! A hardy congratulations on the launch!
Jim Engine
Very nice, exactly what I was looking for. @antwilson (The platform as a whole with all the awesome benefits) 👌
Alex Zirbel
Awesome! We do a lot of vector search with Postgres, great to see this available on Supabase.
Bo Lu
That's awesome. The pgvector brings true AI power to Postgres communities!
Tyler Shukert
This is huge! I tried it already and it's so easy to get started with!
Kshitij Minglani
Big Congrats Paul & Ant :)
Ahmad Ali
Surely looks amazing! Congrats on the launch
Johan Steneros
This looks promising. I am sending this over to my dev team.
Atharva Bondre
Storing vector embeddings at scale alongside user data can be beneficial for applications that rely on machine learning algorithms, natural language processing, recommendation systems, or any task involving similarity matching or clustering. The fact that Supabase Vector works with any language, stack, or programming environment is advantageous as it allows developers to integrate it seamlessly into their existing tech stacks without any restrictions. This flexibility can save time and effort when implementing AI functionality. The availability of example projects is a helpful resource for developers, especially those who are new to AI or looking for inspiration on how to leverage vector embeddings effectively. These projects can serve as starting points and references for building AI applications using Supabase Vector. The option to start for free on the Supabase cloud provides an accessible entry point for developers to experiment and evaluate the toolkit's capabilities without immediate financial commitments. Overall, Supabase Vector seems to offer a combination of features that can empower developers to leverage vector embeddings and integrate AI functionality into their applications efficiently. It may be worth exploring further and considering for projects that require scalable vector storage and AI capabilities.
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