Data for AI grounding and RAG

AI grounding and retrieval-augmented generation give assistants and agents fresh, accurate information at the moment they answer. Instead of relying on what a model memorised, the system retrieves licensed content and cites it.

RAG and grounding data provides licensed content through retrieval APIs or feeds designed for AI use, with freshness and citation metadata. News data adds timely articles and extracted entities, which matters for questions about current events and companies. Web-scraped datasets supply structured facts from public websites, such as product details or company information, that an assistant can look up.

A typical workflow

1. Decide which questions need external knowledge and how fresh it must be.
2. Choose sources whose licence allows retrieval and display in AI answers.
3. Index them or connect through an API or MCP server.
4. Monitor answer quality, citations and source coverage.

What to check before you buy

Ask whether the licence covers retrieval, summarisation and display to end users, and whether it limits how much text can be shown. Check update frequency, latency, attribution requirements and whether content may be stored in your vector index or must be fetched live.