Pinecone for Production RAG

Pinecone is the most popular managed vector database for production AI applications. Its serverless architecture and developer experience make it an excellent choice for teams that want to focus on building applications rather than managing infrastructure. At Tensorplay, we’ve built dozens of production RAG systems on Pinecone.

What we handle for you:

• Index design and namespace strategy for multi-tenant applications
• Efficient embedding pipeline setup with batching and rate limit handling
• Metadata filtering architecture for complex access control patterns
• Hybrid search implementation combining dense and sparse vectors
• Index performance tuning and cost optimization (pod vs. serverless selection)
• Data freshness patterns — real-time updates, incremental indexing, and delta sync
• Monitoring index health, query latency, and recall metrics in production

Getting the Pinecone architecture right from the start prevents expensive rewrites later — namespace design and metadata schema decisions in particular are hard to change once production data is loaded.