pinecone
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
| Field | Value |
|---|---|
| Owner | Orchestra-Research |
| Curator | Thomas Cherickal |
| Source | Orchestra-Research/AI-Research-SKILLs |
| Repo stars | 14,542 |
| License | MIT |
| Repo last push | 2026-10-11 |
Links
- Roles: rag-engineer
- Source repo: Orchestra-Research/AI-Research-SKILLs
- Same repo: axolotl, deepspeed, distributed-llm-pretraining-torchtitan, fine-tuning-openvla-oft, fine-tuning-serving-openpi, awq-quantization, gguf-quantization, gptq
- Registry seed skills for this role: rag-engineer seed skills
