Pinecone team. Photo: Pinecone Systems

Pinecone announces $28 million Series A for search technology solution

The Israeli startup’s vector database product provides the search infrastructure for engineering teams to easily implement AI-powered search into their applications without the need to build their own or modify legacy infrastructure

Pinecone Systems, which develops search infrastructure, announced on Tuesday the completion of a $28 million Series A funding round led by Menlo Ventures, with participation from new investor Tiger Global and previous investors including Wing Venture Capital, who led the company’s seed-stage financing.
Pinecone was founded by former Amazon developers and its vector database helps companies handle data ranging anywhere from hundreds of thousands to billions of items. The company has offices in New York and Tel Aviv and will utilize the funding to grow out its product, customer success, and R&D teams, and will invest in core research on machine learning (ML), information retrieval (IR), and natural language processing (NLP).
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Pinecone team. Photo: Pinecone Systems
(צילום: פיינקון סיסטמס)
“Search technology has revolved around keywords for hundreds of years; books contained search indexes before the invention of the printing press. Amazingly, today’s predominant search infrastructure still works the same way,” said Edo Liberty, Founder and CEO of Pinecone. “Today’s users expect more. They want search results that anticipate and understand their needs, and not just match keywords.”
The content stored in consumer and enterprise applications is only valuable if users can find it. Traditional keyword-based search systems struggle with complex data such as unstructured text, user profiles, or images. Yet complex data is only growing, as are customers' expectations. That puts pressure on engineering teams to modernize their search systems.

Vector Search is focused on storing and searching through AI-generated representations of content. These AI-generated representations encapsulate the meaning of the original content in a machine-readable format, and enable developers to build better search applications. Pinecone’s vector database product provides the search infrastructure for engineering teams to easily implement AI-powered search into their applications without the need to build their own or modify legacy infrastructure.
“Machine learning has changed the way we interact with our data, and those who don’t react quickly enough will be left behind,” added Liberty. “The importance of vectors in search applications moving forward cannot be overstated, and Pinecone has removed the huge infrastructural barrier that has prevented many companies from benefiting until now.”