Similarity Search as a Service

Search through billions of items for similar matches to any object, in milliseconds.
It’s the next generation of search, an API call away.

Pinecone: Similarity Search as a Service
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Want a demo or have questions? Contact us.

Deploy

Launch a distributed similarity search service in a few lines of code.

Managed
Create a service and start making API calls — leave the infrastructure and ops to us.

Scalable
Each service is persistent, consistent, sharded, and replicated across many nodes.

Sample code for deploying Pinecone.
Sample code for indexing vectors.

Index

Dynamically load and index billions of vector embeddings.

Centralized
Load vector embeddings in streams or batches from models, data lakes, or feature stores.

Fresh
Update from anywhere. New and updated items become searchable in milliseconds.

Search

Run similarity search in Python or Java applications, or notebooks.

Fast
Latency of <50ms, even with billions of items and thousands of queries per second.

Accurate
Our fast search algorithms find more accurate results than open-source options.

Sample code for searching vectors.

Secure

Pinecone runs on hardened AWS infrastructure. Data is stored in isolated containers and encrypted in transit.

Ask us about VPC deployments on AWS or GCP.

Managed

Data persistence, eventual consistency, automatic node recovery, replication, sharding, and more. All done for you.

Cost-Effective

Only pay for what you use, as you go. The efficiency of our vector index leads to lower operating costs.

Use cases for similarity search

Recommendation System

Search for most-liked content or products by similar customers.

Image Search

Index image catalogs and search for similar or related images.

Question Answering

Search for the most similar questions and their answers.

Personalization

Personalize experiences most similar to a user's preferences.

Audio Search

Index audio catalogs and search for similar or related audio.

Deduplication

Find nearly identical records to any specific item.

Semantic Search

Index documents and search for semantically similar content.

Classification

Classify or label items based on similar, already-classified items.

Fraud Detection

Compare a user's behavior with fraudulent patterns.

Anomaly Detection

Index events, then check for dis-similarity with expected events.

Candidate Search

Index candidates and search for closest matches to some profile.

What will you build?

Get started or contact us for a customized demo.