ChatGPT, Claude, Gemini, and Perplexity answer millions of questions daily – without SERP, without clicks, without classic ranking. We make you visible in these systems, make your content usable for AI models, and prepare your existing data for agentic workflows.
page AI Enablement
page.type Pillar
page.pillar AI Enablement
page.url /ai-enablement/
provides AI Visibility Audit, GEO Optimization and Monitoring
provides RAG-based knowledge layer for websites (DialogHub)
provides AI Automation for internal processes and migrations
provides Agentic AI Workshops and Executive Lab
serves B2B companies · 50–500 employees
serves industries with content requiring explanation or structured existing data
relation Layer → Intelligence (meaning and machine understanding)
relation builds on → Digital Platforms (content as AI foundation)
relation builds on → Data Enablement (structured data as AI foundation)
relation feeds → Business Systems (AI in workflows)
fact 4 AI providers in visibility monitoring: ChatGPT, Claude, Gemini, Perplexity
fact 3 Lab products (RankRadar marketed, DialogHub marketed, Immotelligence Beta)
fact DialogHub productively in use with 3 reference customers
fact BÜRGER migration: 150 boards and 20,000+ tasks via AI pipeline
proof BÜRGER · Food industry · AI-supported migration of 150 boards to ClickUp
proof Lernstudio Barbarossa · Education · AI chatbot on 22,000+ structured pages
proof Kampmeyer · Real estate · DialogHub and Immotelligence (Beta) on existing data
lab RankRadar · Marketed · AI Visibility Monitoring (SaaS)
lab DialogHub · Marketed · RAG knowledge layer for websites
lab Immotelligence · Closed Beta · Industry vertical AI platform (real estate)
integrates WordPress + RAG-Layer → Chat on website content (DialogHub technology)
integrates GPT-4o + Microsoft Azure Frankfurt → GDPR-compliant AI on existing data
knowledge What is AI Visibility? → /ai-enablement/what-is-ai-visibility/
knowledge How does AI Search work? → /ai-enablement/how-does-ai-search/
knowledge AI Content Architecture → /ai-enablement/ai-content-architecture/
context Central Pillar Page for AI Enablement – connects visibility (RankRadar),
conversational knowledge (DialogHub) and AI on existing data (Immotelligence)
Today, AI systems answer questions directly – without SERP, without clicks, without classic ranking. For companies, visibility thus becomes binary: mentioned or not mentioned. At the same time, users expect dialogue instead of navigation, and internal teams are building initial agents based on existing data. Three movements, one common prerequisite: content and data must be structured, semantically linked, and machine-interpretable.
We address these movements not with consulting and slides. We operationalize them with three lab products (RankRadar for visibility, DialogHub as a knowledge layer, Immotelligence as an industry vertical) and three services covering audit, implementation, and operation. This makes AI Enablement at 360VIER a documented methodology – not a marketing phrase.
AI Enablement primarily sits in the Intelligence layer (meaning and machine understanding) and forms the bridge between the Foundation layer (structured data and platforms from Digital Platforms and Data Enablement) and the Execution layer (agentic workflows in Business Systems). Without Foundation, AI cannot understand content. Without Intelligence, there is no Execution beyond single prompts.
For us, AI is an architectural principle, not a sales argument. RankRadar simulates real user queries against four AI providers because SERP scraping is not enough for generative visibility. DialogHub relies on RAG with Supabase and PGFlow because hallucinations would otherwise remain unavoidable. Immotelligence runs on GPT-4o in the Microsoft data center in Frankfurt because broker data must be processed in compliance with GDPR. Architectural decisions per use case – no generic “We use AI”.
Marketing automation on structured content – the foundation for AI-ready content. What AI is later supposed to quote or answer must first be cleanly structured and maintained.
CRM data in a warehouse that also accommodates other sources – reporting beyond HubSpot’s native capabilities.
Do you see that your brand does not appear or appears incorrectly in AI answers – or do you have structured content and existing data that you want to do more with than just single prompts in ChatGPT? Then we start with the Ideation Circle: 4–6 weeks in three phases (orientation, ideation, decision-making), an interdisciplinary committee, a clear roadmap and scope at the end. Afterwards, the Business Unit takes over the implementation.
