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Pinecone Launches Innovative Vector Database with Inference Capabilities
Pinecone Launches Innovative Vector Database with Inference Capabilities
Database Dreams Disrupted

Pinecone Launches Innovative Vector Database with Inference Capabilities

Founded in 2019, Pinecone has raised a total funding of $138M.

Published Updated

Key takeaways

  • Pinecone integrates industry-first inference capabilities into its vector database for enhanced AI application accuracy.
  • New features improve AI application development, achieving up to 48% increased accuracy and faster tool creation.
  • Enhanced security includes granular role-based access controls and customer-managed encryption keys for data protection.
  • Pinecone's platform now offers proprietary models and a new sparse vector index type for advanced retrieval.
  • Collaboration with Amazon Bedrock enables automated data handling for large language model integration.
5 min

Pinecone, a leading knowledge platform for building accurate and scalable AI applications, has announced the integration of industry-first inference capabilities into its vector database. 

This new feature includes fully-managed embedding and reranking models and a unique approach to sparse embedding retrieval. By combining these capabilities with Pinecone’s dense retrieval technology, the platform sets a new standard for AI-powered solutions with cascading retrieval.

The company said these new advancements aim to improve the development of AI applications, making them up to 48% more accurate and enabling faster and easier creation of AI-driven tools. 

Pinecone has also introduced more granular role-based access controls (RBAC), allowing users to set API key roles for enhanced control over data plane operations. Customer-managed encryption keys (CMEK) provide users with greater control over their data encryption, improving tenant isolation. Additionally, audit logs for control plane activities and the general availability of AWS PrivateLink for serverless indexes further enhance security and performance.

Pinecone’s composable platform now includes pinecone-rerank-v0 proprietary reranking model, pinecone-sparse-english-v0 proprietary sparse embedding model, 

new sparse vector index type and includes new security features. 

AWS Collaboration

Through its collaboration with Amazon Bedrock, Pinecone offers seamless integration that automates the ingestion, embedding, and querying of customer data as part of the large language model generation process. This integration allows customers to quickly generate more grounded and production-grade AI applications while running Retrieval-Augmented Generation (RAG) evaluations natively within Amazon Bedrock, eliminating the need for third-party tools.

Pinecone’s innovative approach combines inference, retrieval, and knowledge base management on a single platform, leading to significant performance improvements and new possibilities for AI application development. Customers can access Pinecone through the AWS Marketplace to accelerate deployment and optimise costs, further empowering developers to deliver better AI solutions.

Pinecone, claims to have already helped over 5,000 customers build faster, more confident AI applications. 

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