Perplexity
Search & ResearchAnswer engine with cited sources
FreemiumDeekoya Pick
Examples: review, pricing & alternatives
Pinecone Database is a search engine for AI agents and applications, built for semantic search, knowledge retrieval, and long-term memory at scale. It provides Jupyter Notebook examples to help users get hands-on with Pinecone vector databases.
What is Examples?
Pinecone Database is a search engine for AI agents and applications, built for semantic search, knowledge retrieval, and long-term memory at scale. It provides Jupyter Notebook examples to help users get hands-on with Pinecone vector databases.
Best for
- Semantic search for AI-driven applications
- Knowledge retrieval in large document collections
- Long-term memory storage for autonomous agents
- Hybrid search scenarios combining vector and keyword queries
Examples features
- Create and configure indexes
- Data modeling and ingestion
- Semantic, hybrid, and sparse-vector search
- Integrated embedding and metadata filtering
- Rerank results to increase relevance
- Manage indexes, namespaces, and backups
- Cost management tools (spend alerts, usage reports)
- Bring Your Own Cloud (BYOC) and security enforcement
Examples pricing
The official site lists the pricing as "Free"; this information was read from the official site.
Sources: official homepage · last checked 2026-10-26. Prices can change; confirm on the official site.
How to use Examples
- Visit the Pinecone documentation and select "Get started" to create an account.
- Follow the "Index data" guide to model and ingest your documents.
- Use the "Search" section to perform semantic, hybrid, or sparse-vector queries.
- Configure cost controls in "Manage cost" to set spend alerts and download usage reports.
- Deploy your index to production using the "Move to production" instructions.
Examples pros and cons
Pros (from the official site)
- Supports multiple search types (semantic, hybrid, sparse-vector)
- Integrated embedding generation
- Robust cost-management features
- Namespace and backup management
Limits stated on the site
None stated on the official site.
Latest Examples updates
RSS feed- How to start a personal blog in 7 steps, plus real examples
Official blog / changelog · 2026-12-18
- Agentic AI examples in marketing and video
Official blog / changelog · 2026-10-22
- API documentation: What it is and how to write it (with examples)
Official blog / changelog · 2026-10-19
- Translation: What it is, how it works, types, & examples
Official blog / changelog · 2026-10-16
Examples alternatives
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Examples comparisons
Examples FAQ
What is Examples?
Pinecone Database is a search engine for AI agents and applications, built for semantic search, knowledge retrieval, and long-term memory at scale. It provides Jupyter Notebook examples to help users get hands-on with Pinecone vector databases.
Is Examples free?
Yes. Examples's official website mentions a free plan, free tier or trial (checked 2026-10-26).
How much does Examples cost?
The official site lists the pricing as "Free"; this information was read from the official site.
How do I use Examples?
1. Visit the Pinecone documentation and select "Get started" to create an account. 2. Follow the "Index data" guide to model and ingest your documents. 3. Use the "Search" section to perform semantic, hybrid, or sparse-vector queries.
What are the best alternatives to Examples?
Alternatives in Search & Research include Perplexity, NotebookLM, Zep, Ai Knowledge Graph, Graph Fraud Detection Papers.
Written from Examples's official website (checked 2026-10-26); nothing here is sponsored. Want to master tools like this? See the 100+ AI Tools Course.