Pinecone's unique serverless vector database slab architecture — with Dedicated Read Nodes now generally available — gives customers exceptional price-performance for any use case

NEW YORK, April 15, 2026 /PRNewswire/ – Pinecone, the leading vector database, today announced that its next-generation serverless slab architecture and newly released Dedicated Read Nodes (DRN) are powering real-time, AI-driven contact recommendations for sales and marketing teams. With Pinecone, ZoomInfo now serves highly relevant suggestions instantly, driving a 50% increase in user engagement and enabling customers to identify the right buyers in minutes instead of hours.

Companies across industries are racing to operationalize AI, yet they increasingly face a core infrastructure challenge: every AI use case has different performance, concurrency, latency, traffic, and cost requirements. Databases with bolted-on vector capabilities struggle at scale because they were never designed for high-throughput semantic or hybrid search, while open-source vector databases often require deep ANN tuning, cluster management, and complex operational overhead. Neither approach can efficiently support the diverse, production-grade workloads enterprises now run. Pinecone’s serverless architecture — which includes On-Demand indexes, where storage scales elastically and customers pay only for the queries they make, and Dedicated Read Nodes for sustained high queries per second (QPS), low-latency workloads — eliminates these constraints and lets teams optimize price-performance for every use case.

Dedicated Read Nodes, generally available today, provides resource isolation and guaranteed warm data which prevents delays caused by cold fetches. This ensures predictable low-latency performance even under sustained high-QPS production workloads, which has been difficult for vector databases until now. Combined with Pinecone’s slab architecture, which stores vectors in large contiguous units to avoid fragmentation and ensure consistent performance, customers benefit from purpose-built managed infrastructure that delivers superior price-performance across all of their AI applications.

ZoomInfo selected Pinecone to power its new real-time recommendation engine, which now serves personalized contact suggestions across more than 390 million and growing high-dimensional embeddings and over 100,000 namespaces. With Pinecone, the Applied AI team moved from prototype to production in weeks, meeting strict sub-second latency requirements and achieving an order-of-magnitude improvement in throughput during scale testing with Dedicated Read Nodes. Pinecone enabled ZoomInfo to deliver a 50% increase in user engagement, a 2x improvement in relevancy and recall, and the ability to handle 50x more peak request volume, all while maintaining predictable low-latency performance. These improvements dramatically reduced ZoomInfo’s customer time-to-action, cutting workflows that previously took hours down to minutes by surfacing the right contacts instantly.

“Pinecone’s slab architecture and Dedicated Read Nodes gave us the speed, consistency, and isolation we needed to run real-time recommendations at scale. Instead of managing infrastructure, we spend our time improving our recommendation model and the product itself. That has reduced the time our customers spend researching, filtering, and evaluating contacts—from hours to minutes—by giving them the right people to reach out to with a single click.” — Carlos Nunez, Vice President of Engineering and Applied AI at ZoomInfo

Ash Ashutosh, CEO of Pinecone, emphasized the broader market significance:

“Every company today has multiple AI applications, and each one has different performance and cost profiles. Pinecone is the only vector database that lets customers run all of these workloads in one place, with exceptional speed, accuracy, and cost efficiency at scale. Our serverless slab architecture and Dedicated Read Nodes deliver trusted knowledge to our customers and make it possible to deploy production-grade RAG, search, recommendation systems, and agents without compromise.”

With Pinecone’s unique architecture, enterprises no longer face tradeoffs between price, performance, and scale. ZoomInfo’s deployment illustrates how organizations can use Pinecone to ship AI applications faster, improve user experiences, operate reliably at massive scale, and create experiences that previously weren’t possible.

To see how Pinecone powers real-time recommendations at enterprise scale, read the full ZoomInfo case study. For more information about Dedicated Read Nodes and how they unlock predictable low-latency performance for your most demanding workloads, see here.

About Pinecone

Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone's mission is to make AI knowledgeable. More than 9000 customers across various industries shipped better AI applications faster and more confidently with Pinecone's technology. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. For more information, visit pinecone.io.

Media Contact:

Mike Sefanov
mike.s@pinecone.io
Sr. Director, Communications