Pinecone is the fastest way to get a managed vector index into production — no cluster to run, no capacity planning. The work that actually determines whether search results are useful is everything around the index: chunking strategy, metadata filtering, and namespace design. We build that layer.
A managed vector database still needs a well-designed pipeline feeding it.
Pinecone handles infrastructure — we handle the chunking, embedding model choice, and metadata filters that decide whether search actually returns the right document.
Namespace and pod-size decisions made upfront so your Pinecone bill scales with usage, not with avoidable over-provisioning.
End-to-end integration with your LLM of choice — ingestion, retrieval, and re-ranking wired together and tested against real queries.
Moving from a self-hosted vector store or prototyping tool to Pinecone without losing embeddings or downtime on a live product.
Scoped to your pipeline, not a fixed package.
Structuring indexes and namespaces around your data model and query patterns, not a generic default.
Chunking strategy and embedding model selection tuned to your content type and retrieval goals.
Combining vector similarity with metadata filters so results stay relevant as your dataset grows.
Connecting Pinecone to your LLM application with retrieval, re-ranking, and prompt assembly that actually improves answers.
If you want zero infrastructure to manage and predictable scaling, Pinecone is the simpler choice. If you need full control over hosting, cost at very large scale, or data residency, a self-hosted option like Qdrant or Weaviate may fit better. We look at your data volume and ops capacity before recommending either.
It depends on how much of the pipeline already exists — a straightforward integration into an existing RAG setup costs less than building ingestion, chunking, and retrieval from scratch. We give a fixed estimate after a short scoping call.
Semantic search, RAG-based chat and Q&A, recommendation systems, and deduplication — anything where you need fast similarity search without wanting to operate the underlying infrastructure yourself.
Tell us what you're building and what's in your current pipeline — we'll scope an approach and a fixed estimate.