Laravel 13 tutorial shows how to build a full PDF-to-AI-answers pipeline with pgvector

A developer tutorial published on DEV Community walks through building a document question-answering system using Laravel 13, covering the full pipeline from file upload to AI-generated answers. Users can upload PDFs, Word files, emails, and scanned documents, which are converted to Markdown, split into chunks, and stored as vector embeddings in a Postgres database using the pgvector extension. The guide uses two packages — Laravel's built-in AI SDK for embeddings and agents, and a third-party hosted parsing API called Parse for Artisans to handle OCR and non-digital file formats. The author notes that teams dealing only with digital PDFs can substitute the paid parsing service with the free spatie/pdf-to-text package, though it cannot process scanned documents or non-PDF formats. No separate vector database is required, as all embeddings are stored directly in Postgres.