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About
Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your retrieval augmented generation system. Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate. Build a real-time personalized ecommerce product feed with user vectors constructed from SKU embeddings the user interacted with. Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook.
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About
Open-source vector similarity search for Postgres.
Supports exact and approximate nearest neighbor search for L2 distance, inner product, and cosine distance.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Organizations wanting a data engineer solution to turn data into vector embeddings
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Audience
Developers interested in an open source vector similarity search for Postgres
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Open source
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationSuperlinked
Founded: 2021
United States
superlinked.com
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Company Informationpgvector
github.com/pgvector/pgvector
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Categories |
Categories |
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Integrations
Apify
Cake AI
Langtrace
MyDBA.dev
Nebius Token Factory
PostgreSQL
Python
Supabase
Superexpert.AI
Weaviate
|
Integrations
Apify
Cake AI
Langtrace
MyDBA.dev
Nebius Token Factory
PostgreSQL
Python
Supabase
Superexpert.AI
Weaviate
|
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