https://video.ut0pia.org/videos/watch/a4d36f74-a134-4ff0-9654-c602b7399678 Building a prototype chatbot interface takes an afternoon, but scaling it into a secure, predictable enterprise app requires solving production infrastructure challenges: minimizing unpredictable cloud API token bills, handling broken layout extractions, mapping session telemetry, and executing deterministic search. In this practical, demo-driven session, we will bypass high-level wrapper libraries to dissect the complete technical implementation of a local-first document ingestion application. While our demo runs on local developer environments, the underlying design patterns mirror exactly how you build high-performance, cost-effective architectures using enterprise infrastructure like Azure Database for PostgreSQL with pgvector. Key Architectural Blueprints We Will Explore: Optimizing the Data Ingest: How parsing documents to clean structural Markdown locally eliminates cloud vision token overhead. We will look at implementing dynamic sidebar toggles to switch into heavy-duty local OCR pipelines when corrupted document font layers are encountered. Database-First RAG without Framework Bloat: Why heading-based semantic chunking outperforms arbitrary sliding token windows. We will walk through the raw SQL schemas and indexes (HNSW tracking) required to combine dense embedding vectors and sparse keyword text indices natively inside a single database query, using Reciprocal Rank Fusion (RRF) for top-tier retrieval performance. UX Telemetry and Application Guardrails: A deep dive into injecting live client-side floating widgets to display session telemetry, tracking token limits and cumulative ROI. Finally, we will touch on building a zero-dependency, background-threaded heuristic validation layer (_check_injection()) to scan incoming Markdown text for prompt-injection markers before they hit your persistence layer. Speakers: Abed Matini (Ogilvy): Abed Matini is a software developer and AI engineer focused on practical RAG systems, with a strong emphasis on local and edge LLMs and lightweight production architectures. X/Twitter: https://x.com/abedmatini LinkedIn: https://www.linkedin.com/in/matini GitHub: https://github.com/abedmatini Mon, 29 Jun 2026 15:58:19 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/a4d36f74-a134-4ff0-9654-c602b7399678 All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.