> ## 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.

# Reducto

> Worlds vs Reducto: RDF fact ledger vs document extraction pipeline.

## At a glance

|               | Worlds                                                | [Reducto](https://reducto.ai)                        |
| :------------ | :---------------------------------------------------- | :--------------------------------------------------- |
| Primary role  | Authoritative RDF fact ledger & SPARQL context engine | Document processing API & layout-aware parser        |
| Data model    | RDF triples in an append-only graph ledger            | Extracted JSON schemas, markdown, & bounding boxes   |
| Retrieval     | SPARQL graph queries, full-text, & vector fusion      | Document chunk search & structured JSON extraction   |
| Core strength | Deterministic multi-hop SPARQL graph verification     | Complex document parsing (PDFs, tables, forms, scan) |
| Deployment    | Edge-ready adapters (LibSQL, Postgres) or Cloud       | Managed Cloud API                                    |

## Overlap and shared capabilities

Both Worlds and [Reducto](https://reducto.ai) solve critical problems in the AI
document processing and retrieval pipeline. Both systems convert unstructured
content into machine-readable structures so AI agents spend fewer tokens
retrieving context and avoid hallucinated values.

The key distinction lies in where each system operates:

* Reducto is a document parsing engine. It ingests complex, unstructured
  documents (PDFs, multi-page financial forms, scans) and extracts visual
  layouts, tables, and structured JSON schemas with high fidelity.
* Worlds is an authoritative RDF fact engine. It takes verified assertions,
  links them into an append-only RDF triple store, and provides SPARQL graph
  queries alongside vector and full-text search.

Reducto acts as an ingestion bridge, turning complex raw files into structured
assertions that can be loaded directly into Worlds as verifiable facts.

## When Worlds fits

* You need deterministic graph querying (SPARQL) to verify multi-hop
  relationships across enterprise domain facts.
* You require immutable provenance, audit trails, and quad-level assertion
  tracking.
* You want open-standard RDF schemas that operate natively across edge adapters
  (LibSQL, Postgres) and cloud infrastructure.

## When Reducto fits

* You need high-accuracy parsing of visually complex PDFs, tabular data, or
  scanned forms.
* You require bounding-box layout detection and chunking before passing document
  content to LLMs.
* You are building an upstream document extraction pipeline prior to context
  storage.

## Coexistence and integration

Reducto and Worlds complement each other cleanly. In an enterprise pipeline,
Reducto parses unstructured documents into structured JSON entities and
key-value tuples. Those assertions are then imported into Worlds as RDF quads.
Agents can then query Worlds via SPARQL and hybrid search to retrieve
verifiable, interconnected knowledge.