Pinecone turns unstructured data into knowledgeable AI for developers with Microsoft Azure

Facing rapid growth, Pinecone partnered with Microsoft Azure for seamless integration, dynamic scaling, and more efficient AI applications.

Pinecone chose Microsoft Azure for secure, scalable AI processing with seamless integration, unified billing, and single sign-on for more efficient data management and AI development.

Pinecone’s Microsoft Azure integration boosts AI accuracy, scalability, and efficiency supporting thousands of weekly new signups weekly. It enables real-time data retrieval, reduces latency, lowers costs, and simplifies deployment with unified billing, single sign-on, and templates.

Pinecone’s mission to make AI more knowledgeable continues to gain momentum. A developer and product-led growth business, Pinecone sees thousands of weekly new signups. These new signups are eager to use a powerful vector database designed to transform unstructured data, such as text, images, audio, video, PDFs, emails, etc. By enabling real-time data processing with low latency, developers can overcome key challenges in AI accuracy and create more seamless user experiences.

To support Pinecone’s growth demand, they’ve partnered with Microsoft Azure to offer a native integration. This collaboration provides developers with a streamlined experience, including unified billing, single sign-on, and built-in Microsoft templates to accelerate project development. Now discoverable directly in the Microsoft commercial marketplace, Pinecone empowers developers to harness unstructured data efficiently and deliver more accurate and performant AI solutions at scale.

As Adel Farahmand, VP, Business Development & Partnerships of Pinecone explained, “About 80% of the data out there is unstructured in nature. What we do is retrieve that information, provide deep semantic-based understanding of it, and then make that something developers can use for search-based use cases, Retrieval-Augmented Generation (RAG), agents, recommender systems, and more.”

“About 80% of the data out there is unstructured in nature. What we do is retrieve that information, provide deep semantic-based understanding of it, and then make that something developers can use for search-based use cases, Retrieval-Augmented Generation (RAG), agents, recommender systems, and more.”

Adel Farahmand, VP, Business Development & Partnerships, Pinecone

AI-powered applications, such as chatbots, assistants, and search tools, tend to face challenges when it comes to accuracy. This problem manifests into what is called “hallucinations” or, simply put, incorrect or nonsensical responses that can seem accurate at first glance. Most models achieve between 70 to 80% accuracy, making their usefulness limited. A key factor contributing to these inaccuracies is the quality and availability of real-time knowledge.

Customers use Pinecone’s developer-friendly vector database to address these challenges for mission-critical workloads. The result is that AI models have access to up-to-date information that enhances accuracy and performance at scale across various use cases such as search, RAG, and agents.

Pinecone focuses on simple APIs, robust documentation, and active developer advocacy. Its platform has evolved from a search-centric solution to supporting cutting-edge AI use cases, powered by a high-scale, multimodal vector database. Partnerships with industry leaders like NVIDIA have contributed to the integration of re-rankers and embedding models directly into the database, reducing latency, lowering costs, and accelerating time to market. With a new native integration with Microsoft Azure, Pinecone further simplifies the developer experience.

Scaling AI solutions for real-time data retrieval

Pinecone stands out in the crowded field of vector databases by focusing on performance at scale, real-time data retrieval, and advanced architecture for production workloads. While many vector databases cap handling at 100 to 300 million vectors, Pinecone supports workloads operating at tens of billions, making it ideal for large-scale applications.

Multi-tenancy and fresh data without re-indexing

A key innovation is Pinecone’s namespace design and data freshness layer. With namespaces, customers can separate their vector index across tens of thousands or millions of partitions (namespaces) allowing customers to develop AI solutions for all of their end users. The data freshness layer means unlike traditional systems that require re-indexing every time data is updated, Pinecone uses a node-based architecture that allows immediate data retrieval. This is critical for dynamic industries like advertising and marketing, where real-time access to constantly changing data is essential.

Serverless architecture for better performance

Initially built with a pod-based architecture, Pinecone re-architectured its platform to a serverless structure in response to the surge in customer demand. This shift allowed for improvement in accuracy, efficiency, and a developer friendly - easy to use database design. By integrating re-rankers and embedding models, Pinecone further reduces latency, and enhances information retrieval.

Next-level AI solutions

Pinecone has also introduced products like Pinecone Inference for improved accuracy and grounding, as well as Pinecone Assistant for grounded chat and agent-based applications that abstract away the many systems and steps required to build Retrieval Augmented Generation (RAG)-powered applications such as chunking, embedding, file storage, query planning, vector search, model orchestration, reranking, and more. By combining scale, speed, and intelligent architecture, Pinecone empowers developers to build smarter AI applications that process vast, dynamic datasets seamlessly.

Empowering developers through partnership and marketplace

Pinecone’s partnership with Microsoft Azure offers developers flexible pay-as-you-go pricing, allowing thousands of weekly new signups to scale workloads without upfront commitments. This serverless architecture enables dynamic scaling, reducing costs and complexity.

The Azure integration with Pinecone also streamlines work for developers with tools like single-on and out-of-the-box templates. Pinecone is also available for purchase through the Microsoft commercial marketplace, which provides quick and secure deployment directly through Azure.

Farahmand shared that "The Azure partnership means developers can get started a lot faster on the platform, discover us directly in the [Microsoft commercial] marketplace, and readily just start building on Pinecone.”

This collaboration with Azure fuels smarter, scalable AI solutions tailored to developer needs.

“Azure and Microsoft are immense innovators in the AI space. They’re very aligned with the areas of innovation that we’re continuing to move toward. Azure is a very high security, compliance, enterprise-grade quality standard that we also take very seriously at Pinecone as we think about supporting more of our enterprise customer base,” said Farahmand

“The Azure partnership means developers can get started a lot faster on the platform, discover us directly in the [Microsoft commercial] marketplace, and readily just start building on Pinecone.”

Adel Farahmand, VP, Business Development & Partnerships, Pinecone