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Lesson

Local GraphRAG and graph-based memory

GraphRAG is not a magic word. It helps when relationships matter: people, companies, contracts, records, technical dependencies, or events that change over time.

  • Distinguish when vector search is enough and when a graph adds value.
  • Extract verifiable entities and relationships from documents.
  • Combine graph, chunks, and citations without losing traceability.
Terminal
Entidad:
  id: "cliente:acme"
  tipo: "cliente"
  nombre: "ACME S.L."
  fuente: "contrato-marco.pdf#p4"

Relacion:
  origen: "cliente:acme"
  tipo: "tiene_contrato"
  destino: "contrato:2026-03"
  evidencia: "contrato-marco.pdf#p4"

When it's worth it

  • Questions that span multiple documents or dates.
  • Auditing contracts, invoices, suppliers, or records.
  • Agent memory where who did what and when matters.
  • Technical documentation with dependencies between services.
Advanced Chunking for Private RAGOCR and Tables in Real-World PDFs
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This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
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01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

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Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

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Prepare your environment, work with coding agents, and run models while keeping control of your projects.

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This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

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