I mapped every AI automation opportunity across 25 industries. 10-15 pain points each. With the exact positioning, pricing range, and who to sell to. This took me 4 years and 80+ client engagements to figure out. A lot of AI Agencies pick a niche and pray. They don't know the actual pain points. They don't know who the buyer is. They don't know what these companies are already paying for broken solutions. They don't know what the realistic project size is. So they end up competing on price for generic "AI automation" gigs. I've worked with marketing agencies, recruiting firms, e-commerce brands, law firms, real estate companies, healthcare practices, financial services, SaaS companies, manufacturing, construction, logistics, and more. Every single one has 10-15 processes that are bleeding money because they're still done manually. Here's what the guide covers for each industry: → The top 10-15 automation pain points (ranked by ROI) → Who the actual buyer is (CEO, COO, ops manager, etc.) → What they're currently paying for manual labor or broken SaaS → Realistic project pricing ($5K-$60K+ depending on scope) → The discovery questions that unlock the deal → How to position yourself as the expert even if you've never worked in that industry → Red flags to avoid (industries and company sizes that aren't worth it) 25 industries and 300+ specific automation opportunities. This is the cheat code for picking your niche and knowing exactly what to sell before you ever get on a call. What the full guide? 1. Like this post 2. Comment "NICHE" and I'll send the guide (must be connected) Bonus for the first 100 people: I'm also including an ROI calculator you can use on prospect calls. Plug in their numbers and show them exactly what they're losing to manual work every year.

J'ai indexé 7 600 pages du dossier Epstein dans une IA. En 3 minutes. Depuis HuggingFace. Direct dans IgnitionRAG. Upload. Extraction. Chunking. Embedding. Indexation. Automatique. Et maintenant je peux poser n'importe quelle question en langage naturel sur l'intégralité du dossier. Avec des citations. Des sources. Du contexte. Mais c'est qu'un début. Je suis en train de constituer une bibliothèque de datasets publics interrogeables par IA : → Dossier Epstein (fait ✅) → Textes de lois français → Données INSEE → Code du travail → Jurisprudences → Et d'autres qui vont faire parler... Des données publiques. Accessibles à tous. Mais que personne ne lit. Jusqu'à maintenant. Imaginez une PME qui interroge le Code du commerce en langage naturel. Un avocat qui fouille 10 ans de jurisprudence en 30 secondes. Un journaliste qui croise des milliers de pages de documents déclassifiés. C'est ça le vrai RAG. Pas un chatbot sur votre FAQ. Rendre l'information publique réellement accessible. Et vous, quelles données vous aimeriez pouvoir interroger en langage naturel ? Quel dataset vous feriez tourner sur IgnitionRAG ? Balancez en commentaire. Les plus demandés, je les indexe. 👇