Document Processing
Document processing for RAG pipelines: SFTP and connector ingestion, PDF parsing, OCR, table extraction, and multi-modal document understanding.
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Document Processing
Production documents are messy — PDFs with image-tables, Word docs with tracked changes, HTML full of nav bars. Ingestion is the unglamorous stage where most RAG quality is quietly won or lost.
“Garbage in, garbage out” is not a cliché in RAG — it is the failure mode. Everything downstream (chunking, embedding, retrieval) inherits whatever text this stage produces. A table whose cells got interleaved into gibberish will embed into gibberish and retrieve as gibberish. Time spent here has the highest return of any stage in the pipeline.
Document Ingestion — Handling Real-World Data
Production documents are messy. PDFs have tables rendered as images. Word docs have track changes. HTML has nav bars and footers. Confluence pages embed Jira tickets. The ingestion pipeline must handle all of it.
How Documents Arrive — Connectors & Drop Zones
Before you can parse a document you have to receive it. The transport decides your freshness SLA, how you detect that something changed, and how much of the error budget ingestion burns. “Where does the data come from?” is the first question a good interviewer asks, and the answer is rarely “an API.”