Use Cases
AI in practice, from semantic search to generative chatbot agents.
Pinecone Picks
Semantic search with Pinecone
Unlike keyword-based search, semantic search uses the meaning of the search query. It finds relevant results even if they don’t exactly match the query. This works by combining the power of Large Language Models (LLMs) to generate vector embeddings with the long-term memory of a vector database.
6 min read
Generative Question-Answering with Long-Term Memory
Generative AI sparked several “wow” moments in 2022. From generative art tools like OpenAI’s DALL-E 2, Midjourney, and Stable Diffusion, to the next generation of Large Language Models like OpenAI’s GPT-3.5 generation models, BLOOM, and chatbots like LaMDA and ChatGPT.
8 min read
How to add hybrid search to a Postgres app with Pinecone in 2026
Add hybrid search to a Postgres app with Pinecone: full-text and vector search in one index, Postgres as the source of truth. Built around a snack shop example.
12 min read
Chatbots with Pinecone
Chatbots trained on the latest AI models have access to an extensive worldview, and when paired with the long-term memory of a vector database like Pinecone, they can generate and provide highly relevant, grounded responses.
8 min read
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