Pinecone Leaves Stealth With $10 Million, Launches First Serverless Vector Database for Machine Learning

The Cloud-Native Database for Machine Learning Answers Complex Queries Over Billions of High Dimensional Vectors Accurately and in Milliseconds

PineconeSystems Inc., a machine learning (ML) cloud infrastructure company, left stealth with $10m in seed funding. The investment was led by Wing Venture Capital, and Wing’s Founding Partner, Peter Wagner, will be joining the Pinecone board. Built by the team behind Amazon SageMaker and founded by scientist and former AWS Director Edo Liberty, Pinecone makes large-scale real-time inference as simple as querying a database. It is available for self-onboarding today.

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Pinecone builds infrastructure to enable the next wave of artificial intelligence (AI) applications in the cloud. The company’s vector database supports large scale production deployments of real-time applications such as personalization, semantic text search, image retrieval, data fusion, deduplication, recommendation, and anomaly detection. Each of these is a multi-billion dollar market today and projected to grow 30%+ YoY for the foreseeable future as more and more companies adopt ML technologies.

Modern ML and AI use vectors (aka embeddings) to represent data such as documents, videos, and user behaviors. Applications that need to accurately filter and rank large collections of such vectors in real time require a highly specialized data infrastructure. Existing databases or search engines aren’t a good fit; they are designed for tables and documents, not vectors. In-house systems that use open source libraries are expensive to build and hard to maintain. This forces developers to constantly compromise between speed, accuracy, stability, and scale.

Using Pinecone’s unique vector database, ML and data infrastructure engineers can dynamically transform and index billions of high-dimensional vectors. They can answer queries like nearest neighbor and max-dot-product search accurately and in milliseconds. Pinecone’s database is 100% serverless and API-driven, which means customers always have the computing resources they need, when they need them, without having to worry about infrastructure or maintenance. Simple self-onboarding and consumption-based pricing let companies build proofs of concept with very little overhead and then scale effortlessly.

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One of the largest retailers in the world reports using Pinecone to serve real-time shopping recommendations based on their own deep learning models. They saw an immediate 18.5% lift in revenue per recommendation compared with their previous solution. “Visionary leaders in many companies are working hard to transform their business with machine learning. Pinecone gives them technology they need which, until today, was reserved to a few tech giants,” said Edo Liberty, Founder and CEO of Pinecone.

“The modern Enterprise is built on data and powered by AI. The Data Cloud has emerged as its foundation with the ascendance of Snowflake. Pinecone is poised to unleash data teams and their ML-based applications in a similar fashion,” said Peter Wagner, Founding Partner, Wing Venture Capital.

The Pinecone team knows how to build production grade ML systems. Pinecone’s founder and CEO, Edo Liberty, ran Yahoo’s Scalable Machine Learning Platforms group and later Amazon AI Labs which included a team building Amazon SageMaker. Engineering is led by Amir Sadoughi, a senior AWS engineer and leader who spearheaded the creation of Amazon SageMaker.

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