News, guides and insights on document AI, digital sovereignty and industrial automation.
24 articles
The NATO & French Military Doctrine Dataset offers 377 documents and 29,271 page images with bilingual AI-generated queries for document retrieval and visual question answering. Covers NATO AJP, French TTA, DIA, PIA, and more.
Natotan: multimodal embedding model fine-tuned on Qwen3-VL-Embedding-2B via LoRA. +9% NDCG@1, +6.8% MRR on 5,428 query-document pairs. Bilingual French-English benchmark, 16 categories, 3.3x better than Gemini. Built for military RAG and defense document retrieval.
Technical guide to implement a RAG chatbot connected to product documentation. Architecture, chunking, embeddings and multichannel integration.
Technical implementation of an AI system to automate supplier invoice processing. VLM architecture, structured extraction and ERP integration.
Reduce LLM API costs through semantic caching, intelligent model routing, prompt compression, and request batching without sacrificing quality.
Learn how Graph RAG enhances traditional RAG systems with knowledge graphs, entity extraction, and multi-hop reasoning for enterprise document intelligence.
Architecture and implementation of a monitoring system using AI to correlate alerts, reduce noise and accelerate root cause detection.
Implementation of an AI system to automatically analyze legal contracts. Clause detection, obligation extraction and risk scoring.
Master streaming architectures for LLM applications using Server-Sent Events, WebSockets, and chunked transfer encoding to eliminate perceived latency.