Pinecone provides a fully-managed vector database that helps businesses develop AI applications capable of storing and searching through vector embeddings. This technology allows for a deeper understanding of data, enabling applications like chatbots to retrieve relevant information effectively. By integrating Pinecone's services, chatbots can access the most pertinent context from a company's data, enhancing their ability to respond accurately to user queries. The company offers a scalable business model, starting with a free plan and allowing users to pay based on the resources they consume. Pinecone's services are designed to be user-friendly for developers, eliminating the need for clients to manage infrastructure or troubleshoot algorithms, making it suitable for both small startups and large corporations.

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ICONIQ Growth

Andreessen Horowitz

Enterprise Software

AI & Machine Learning

Pinecone

New proprietary reranking and embedding models, as well as the addition of third-party models like Cohere's Rerank 3.5 model, further provide customers quick, easy access to high-quality retrieval and significantly streamline the development of grounded AI applications."Our goal at Pinecone has always been to make it as easy as possible for developers to build production-ready knowledgeable AI applications quickly and at scale," said Edo Liberty, founder and CEO of Pinecone. "By adding built-in and fully-managed inference capabilities directly into our vector database, as well as new retrieval functionality, we're not only simplifying the development process but also dramatically improving the performance and accuracy of AI-powered solutions."Pinecone's composable platform now includes the following updates:pinecone-rerank-v0 proprietary reranking modelproprietary reranking model pinecone-sparse-english-v0 proprietary sparse embedding modelproprietary sparse embedding model New sparse vector index typeIntegration of Cohere's Rerank 3.5 modelNew security features, including role-based access controls (RBAC), audit logs, customer-managed encryption keys (CMEK), and the general availability (GA) of Private Endpoints for AWS PrivateLinkAdvancing the state of the art for retrievalHigh-quality retrieval is key to delivering the best user experience in AI search and retrieval-augmented generation (RAG) applications. Pinecone's research shows that state-of-the-art performance requires combining three key components:Dense vector retrieval to capture deep semantic similaritiesto capture deep semantic similarities Fast and precise sparse retrieval for keyword and entity search using a proprietary sparse indexing algorithmfor keyword and entity search using a proprietary sparse indexing algorithm Best-in-class reranking models to combine dense and sparse results and maximize relevanceBy combining the sparse retrieval, dense retrieval, and reranking capabilities within Pinecone, developers will be able to create end-to-end retrieval systems that deliver up to 48% and on average 24% better performance than dense or sparse retrieval alone."With the advent of GenAI, we knew we could challenge the status quo in talent acquisition by building an experience focused on the job seeker rather than the hiring company," said Alex Bowcut, CTO of Hyperleap. "With Pinecone, we've seen 40% better click-through rates for the job matches we deliver with search results using their semantic retrieval as opposed to traditional full-text search. Now, with the addition of sparse vector retrieval to Pinecone's proven natural language search capabilities, we're excited to explore how we can bring deeper personalization to people looking for work."Pinecone proprietary modelsWith the introduction of its first proprietary models, Pinecone is making it easier for developers to build knowledgeable AI.Natively integrated into Pinecone's platform, these models simplify the development of production-ready AI applications.AI search simplified with integrated inferenceWith the release of Pinecone's integrated inference capability, engineers can now develop state-of-the-art applications without the burden of managing model hosting, integration, or infrastructure. By offering these capabilities behind a single API, developers can seamlessly access top embedding and reranking models hosted on Pinecone's infrastructure, eliminating the need to worry about vectors or data being routed through multiple providers

First-Of-Its-Kind Pinecone Knowledge Platform To Power Best-In-Class Retrieval For Customers

Pinecone has also announced the general availability of Private Endpoints for AWS PrivateLink.

Pinecone Enhances Vector Database with AI Inference Capabilities

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Pinecone has made a name for itself in recent years as being one of the leading native vector database platforms. Pinecone is continuing to differentiate in an increasingly competitive market with new capabilities to help solve enterprise AI challengesToday Pinecone announced a series of updates to its namesake vector database platform. The updates include a new cascading retrieval approach that combines the benefits of dense and sparse vector retrieval. Pinecone is also deploying a new set of reranking technologies designed to help improve accuracy and efficiency for vector embeddings

Pinecone Expands Vector Database With Cascading Retrieval, Boosting Enterprise Ai Accuracy By Up To 48%

Knowledge platform Pinecone has announced new vector database capabilities combined with proprietary AI models to help developers build more accurate AI applications, faster and more easily.

New platform lets developers build more accurate AI apps faster

With serverless vector database offerings in all three major public clouds (it announced the general availability of its AWS serverless offering in May), Pinecone is positioned to capitalize on the current wave of investment in GenAI, much of which is occurring in the public cloud.

Pinecone Expands Serverless Vector DBs In the Cloud

Pinecone, a vector database for scaling AI, is introducing a new bulk import feature to make it easier to ingest large amounts of data into its serverless infrastructure.

Pinecone previews new bulk import feature for its serverless offering

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. When Edo Liberty was completing his Ph.D. in Computer Science at Yale on random projections, he could have hardly known that a decade later it would be a fundamental component of modern AI.Liberty is the co-founder and CEO of vector database pioneer Pinecone, which has raised over $138 million including a $100 million round in 2023. As it turns out, random projections, which was his thesis topic, is a cornerstone of modern vector search, even as new innovations and use cases for vector databases proliferate. In 2024, vector database technology is no longer a niche or an outlier, but is a required component to enable Retrieval Augmented Generation (RAG) use cases with generative AI. When Pinecone was founded in 2019, vector database technology was not widespread

Pinecone Serverless Goes Multicloud As Vector Database Market Heats Up

We want to hear from you! Take our quick AI survey and share your insights on the current state of AI, how you’re implementing it, and what you expect to see in the future. Learn More. Generative AI was always going to upend search. It’s a technology that can find answers to virtually any question posed to it. And in the process of changing the world of search, AI developers latched on to something else that would meld search and generative AI even more.Generative AI has changed three essential aspects of search: how people ask and look for information, how to get data for answers and how companies can start offering this information to customers.For years, Google has dominated Search. As the dominant search engine (with almost 82% of search traffic), it dictated how users and customers look for information and how brands show up in results

Ai Is Upending Search As We Know It

SAN FRANCISCO, CA / ACCESSWIRE / June 25, 2024 / Robust Intelligence, the AI application security company, announced it would be partnering with Pinecone to integrate with Canopy, their open-source framework which simplifies the development of retrieval-augmented generation (RAG) applications.

Robust Intelligence Partners With Pinecone to Secure Retrieval-Augmented Generation (RAG) AI Applications

Pinecone introduced a serverless RAG product in January 2024, along with claims of 50x cost savings.

OpenAI Acquires Rockset and Highlights Where Generative AI is Headed Next

High-performance vector database for AI applications

Pinecone

High-performance vector database for AI applications

Pinecone

High-performance vector database for AI applications

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