Meana Petro
KC-01FundacionalOla 1IA

Asistente de Conocimiento Técnico (RAG)

En una frase

Ask a question about your own field in Persian, Arabic, English or Spanish and get an answer with the report and page it came from.

El problema

The answer to most operational questions already exists somewhere in the operator’s own archive. Finding it requires knowing which report to look in, which in practice means asking the one engineer who has been there twenty years.

Cómo funciona

Retrieval-augmented generation over the operator’s indexed archive, running entirely on on-premise models. Retrieval is hybrid — dense and lexical — with domain-aware chunking that keeps tables and figure captions intact. Every answer must cite its sources; an answer the system cannot ground in a retrieved document is refused rather than generated, which is the single most important design decision in this capability.

Datos necesarios

  • Indexed document archive from the OCR and classification pipeline
  • On-premise GPU capacity for embedding and generation
  • Access control model defining which users may see which documents
  • A question set from domain experts for evaluation

Qué obtiene

  • Natural-language answers with citations to document, page and passage
  • Source passages displayed alongside every answer for verification
  • Query log showing what people actually ask, which guides archive priorities

Qué no puede hacer

The assistant only knows what is in the indexed archive. It cannot answer a question whose answer was never written down, and it will say so rather than infer. Retrieval quality in Persian and Arabic is measurably below English for the same corpus size, and multi-hop questions that require combining three documents remain a weak point across the industry, not only here.

Cada página de capacidad declara una limitación real. Si un proveedor no puede decirle dónde termina su producto, no le están diciendo la verdad sobre dónde empieza.

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