Pinecone

Pinecone

Build knowledgeable AI
20 reviews21 shoutouts
260 followers

Maker Shoutouts

Testimonials from top launches

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CapybaraDB Beta
Tomo Kanazawa
used this to buildCapybaraDB BetaCapybaraDB Beta
(343 points)
By far the most popular vector database out there! Fast and cost-effective.
Nia
Arlan Rakhmetzhanov
used this to buildNiaNia
(288 points)
One of the best vector databases and easy to work with.
MeetMinutes
Rishi Patel
used this to buildMeetMinutesMeetMinutes
(313 points)
Specifically built to handle vector embeddings, we have ensured high performance in MeetMinutes with Pinecone.
Lambda
Shusuke Takamizawa
used this to buildLambdaLambda
(305 points)
We rely on Pinecone to enhance Lambda's AI-driven data insights and semantic search capabilities. Its scalable and efficient vector database allows us to manage and query large datasets with precision, enabling intelligent search and personalized recommendations.
Kick
Conrad Wadowski
used this to buildKickKick
(668 points)
We needed a trusted vector database for our fine-tuning similarity workflows which deal with a high volume of transactions, documents and other user context. We chose Pinecone for its low-latency, scalability and competitive pricing.
Lookie AI: Make YouTube Your Brain
Steven Oh
used this to buildLookie AILookie AI: Make YouTube Your Brain
(697 points)
It scales like a dream and handles large datasets without breaking a sweat.
iMerch.ai
Kelly Qiu
used this to buildiMerch.aiiMerch.ai
(260 points)
Pinecone’s fast, scalable vector database powers iMerch.ai’s real-time, accurate product recommendations. Its simplicity and AI-focused design set it apart from other solutions.
Magic Patterns
Teddy Ni
used this to buildMagic Patterns [LW24]Magic Patterns
(250 points)
Our vector database used for RAG.
Tim Hillison
used this to buildFleak
(594 points)
A huge shout out to the Pinecone Engineering, Data Science, and Partner teams. We are so excited to be working with you and cleaning up the world's data mess with Fleak & Pinecone! Join us on 8/22 for Pinecone&Fleak workshop for reranking: https://www.pinecone.io/community/events/pinecone-fleakai-workshop/
Outlit AI
Josh
used this to buildOutlitOutlit AI
(376 points)
Pinecone has made it super easily to store massive amounts of vectors and their new serverless tier is very cost effective.
Officely AI
Roy Nativ
used this to buildOfficely AIOfficely AI
(198 points)
We use Pinecone as the main RAG option, but also allow it to work with Bedrock AWS or Azure
Dealwise
Garrett Cahill
used this to buildDealwiseDealwise
(377 points)
We use a hybrid keyword and vector search to identify the best strategic and financial buyers for your business. Pinecone is fast and reliable.
Shortwave
Andrew Lee
used this to buildShortwave AI Email Assistant 2.0Shortwave
(155 points)
It's a great vector db that's fast, cost effective, and supports very large numbers of users efficiently.
Kroolo
Shashank Singh
used this to buildKrooloKroolo
(233 points)
Used for vectorization and vector database, which helps in maintaining the meta properties efficiently.
Inquisite
Jon Reifschneider
used this to buildInquisiteInquisite
(70 points)
Handles our extra-large scale well with low latency
The ORCA Network
Charles Wehan
used this to buildORCA Co-PilotThe ORCA Network
(136 points)
It is the most efficient and cost effective solution!
Belstad — Nonpartisan, AI-Powered News
Josh Lipman
Pinecone's low-latency and scalability makes it the best vector database out there.
M9 Developer
Swanand Rao
used this to buildM9 DeveloperM9 Developer
(52 points)
We used pine cone to build our POC
ARTE
Judd Schoenholtz
used this to buildARTEARTE
(115 points)
Innovators in vector search, easy interoperability with Chat GPT embeddings, flexible scaling options, reliable uptime.
HomeScore
Jared Rosen
used this to buildHomeScoreHomeScore
(206 points)
Helped us get everything built quickly and in an agile way! We love it