Probabilistic metadata extraction error causes RAG chatbot to cite incorrect financial data

A RAG (Retrieval-Augmented Generation) system experienced a "silent hallucination" failure when a probabilistic ingestion extractor produced incorrect metadata during PDF processing. The system ingested thousands of unstructured PDFs, extracted text chunks with metadata (document_type, fiscal_year, company_entity, summary), and embedded them into a vector store. This caused the chatbot to retrieve and confidently cite wrong financial facts — answering 2022 performance questions using 2018 data and misattributing competitors' revenue to the client's subsidiaries.

3h ago1 min readenNews

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Key quotes

A probabilistic ingestion extractor produced incorrect metadata and embedded it into a vector store, causing the chatbot to retrieve and confidently cite wrong financial facts.

After initial success, the chatbot answered 2022 performance questions using 2018 data and misattributed competitors' revenue to the client's subsidiaries.

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