> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wazoo.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Search & Knowledge Graph

> Worlds vs Google Search: self-hostable private agent context vs public web search.

## At a glance

|                  | Worlds                                                | [Google Search](https://developers.google.com/custom-search) & [Knowledge Graph](https://developers.google.com/knowledge-graph) |
| :--------------- | :---------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------ |
| Deployment       | Self-hostable, edge-embeddable (LibSQL), or Cloud     | Proprietary Google cloud infrastructure                                                                                         |
| Scope            | Private domain facts, agent memory, & codebase graphs | Public web pages & global web-scale entities                                                                                    |
| Data model       | W3C RDF 1.1 quads, JSON-LD, & Linked Markdown         | Google Knowledge Graph (Schema.org / Wikidata)                                                                                  |
| Primary consumer | Autonomous AI agents, LLM tool calls, & developers    | Human web searchers, Gemini Assistant, & Google APIs                                                                            |
| Query surface    | SPARQL graph queries, full-text, & vector fusion      | Web search box, Knowledge Panels, & Custom Search API                                                                           |
| Provenance       | Fact-level chronological ledger & exact source quads  | Indexed web URL references                                                                                                      |

## Overlap and shared capabilities

Both [Google Search](https://developers.google.com/custom-search) and Worlds are
built on the same premise: structured knowledge graphs answer queries better
than keyword strings alone ("things, not strings").

* Google Knowledge Graph (launched in 2012) added entity search to the public
  web by mapping entities, attributes, and real-world relationships with
  Schema.org and RDF standards.
* Worlds applies the same RDF graph model to agent memory, so agents can query
  connected entities with SPARQL instead of relying on flat vector embeddings.

The two differ in privacy, self-hostability, and domain scope:

* Google Search indexes the public web for general human information retrieval
  on proprietary cloud infrastructure.
* Worlds is self-hostable and open-source. It manages private enterprise facts,
  local codebases, and agent context graphs on edge databases (LibSQL/SQLite),
  local servers, or private clouds.

## When Worlds fits

* You need to self-host your context engine for data privacy, compliance, and
  air-gapped security.
* You are building AI agents that query private enterprise domain facts,
  codebase structures, or local user state.
* You require deterministic [graph queries](/worlds/query) (SPARQL) to verify
  multi-hop relationships between internal entities.
* You want edge-embeddable context stores (`worlds-libsql`) running directly
  inside your local application runtime.

## When Google Search fits

* You need real-time, global information retrieval across the public internet
  (current events, web pages, external documentation).
* Your application requires broad web-scale entity resolution across world
  facts.

## Coexistence and integration

Google Search and Worlds are complementary tools in an AI agent's toolkit:

* Agents use web search tools (Google Search API, Serper, Tavily, Exa) to
  retrieve live, external information from the open web.
* Agents query Worlds for self-hosted, private domain facts, internal project
  context, and verifiable memory.