--- title: "Agent Experience — MING Labs" description: "AI agents are your new customers. They have budgets, make decisions, and can't use your website. MING Labs opens the doors — Discover, Trust, Act." canonical: https://www.minglabs.com/agent-experience lang: en last-updated: 2026-05-13 --- # AI agents are your new customers. They have budgets. They make decisions. And they can't use a single thing on your website. We open the doors. [Get your Agent Readiness Score](/score) ## Agents don't browse. They query. Every major tech company is building agents. Not chatbots — autonomous actors that research, evaluate, and procure. When they arrive, they ask one question: Who solves this problem? Your configurators, pricing logic, compatibility rules — twenty years of domain knowledge. None of it is in any training set. Agents can't hallucinate it. That's your unfair advantage. But right now, it's locked behind interfaces they can't use. ![From human interfaces to machine endpoints](/_astro/shift-human-agent.BxnbxT1x.svg) ## Three doors to open. Everything you've invested in brand building only counts if these three doors are open. Otherwise, you don't exist to the agent. ### Discover Agents must find you in AI answers, not Google rankings. 15,000 pages of marketing, and the AI cites the competitor with 35 structured answers. We make you citable. Tested across ChatGPT, Perplexity, Claude & Gemini. ### Trust The agent found several options. No brand loyalty. Pure evidence-based comparison: verified claims, structured data, provable accuracy. Brand becomes a reliability score. We build the evidence layer on your domain. ### Act Found you. Trusts you. Now it needs to act. But your configurator runs in JavaScript. Your quote request is a PDF form. We make your tools machine-callable. Same logic, new endpoint, no rebuild. Product configuratorsPricing enginesCompatibility databasesROI calculatorsBooking flowsQuote systemsSpec sheetsAvailability checkers Shopping Agents Price Comparison Product Research Procurement interact with ### Agent Surface: Commerce Product Pages Pricing Data Checkout APIs Talent Agents Job Matching Recruiter Bots Career Advisors interact with ### Agent Surface: Talent Role Profiles Company Culture Application APIs Service Agents Support Bots Returns & Claims Account Mgmt interact with ### Agent Surface: Service Knowledge Base Order History Escalation APIs Comparison Agents Cross-Domain Consistency Check Unified Research interact with ### Unified Agent Surface Taxonomy Cross-Domain Data Single Source built on Discover Answer Pages Citation Audit Query Registry Act Reference Pages ARS Agent APIs Foundation Knowledge Graph Agent Fleet Validation DAX 40 Index Demand ## How agents read your brand. Agent Surface Your brand's machine-readable surface — structured for agents, rendered for humans. Reference Pages anchor your domain expertise as hubs. Answer Pages surround them with discoverable content agents cite, verify, and act through. Agent Fleet Five agent types scanning your brand from different angles — the same way real AI agents do. We test what agents actually see, where you appear, where you don't. The [Agent Readiness Score](/score) and the [DAX 40 Index](/score) both run on this fleet. The more you invest, the wider your surface, the harder you are to displace. ## Same backend. New front door. The Human Journey 01 Website 02 Product Finder 03 ROI Calculator 04 Contact Form 05 Sales Call 06 Quote Rendered UI. Human clicks. Page loads. Works — but invisible to agents. The Machine Journey 01 API Query 02 Structured Response 03 Verification 04 Transaction Same data. Same logic. 100x faster. Millions of simultaneous requests. The Backend: Identical. This isn't a rebuild. It's a new access layer. ## Voices > MING Labs didn't just build a product finder — they changed how our customers discover filtration solutions. The AI handles 3,000 SKUs with a confidence our sales team trusts. Head of Digital MANN+HUMMEL 3,000 SKUs handled ## We built the backends. Now we open them. MING Labs 15 years of digital transformation for industrial enterprises. We built the systems that now need a new front door. UX made them usable for people. We now make them usable for machines. Hyperize We didn't just consult on agent readiness — we built the platform. Hyperize makes brands visible to agents and usable by agents: Answer Pages on your domain, a five-agent fleet that tests what agents actually see, and the Agent Readiness Score that measures all of it. A MING Labs venture. A running product. [hyperize.ai](https://hyperize.ai) ## From score to production in four steps. 1 ### Score We test what AI sees when it searches for your category. Where you appear. Where you don't. What agents can actually do on your site today. [Agent Readiness Snapshot](/score) (free, 48h) or Full Report (detailed, all three doors). 2 ### Strategize Where is your biggest lever? Which doors open first? We map your existing digital infrastructure, identify the highest-impact tools and content, and build a prioritised roadmap. Agent Experience Blueprint with implementation roadmap. 3 ### Build Your tools, your data — made callable for agents. Structured content for discovery, API endpoints for your existing tools, context tracking across touchpoints. No rebuild. New access layer. Production-ready Agent Experience Layer. Typically 90 days. 4 ### Operate How are agents finding you? Which tools are they using? Where are new opportunities? We track, expand, and keep you ahead as the landscape evolves. Monthly performance reports, ongoing optimisation, quarterly reassessment. ## Questions we hear most. Are agents actually buying things today? Not at scale — yet. But OpenAI, Google, and Anthropic are all shipping agent capabilities. Payment protocols are being developed. The question isn't whether this will happen, but whether you're ready when it does. We've invested heavily in our website and brand. Is that wasted? No. Your brand still matters to human buyers. But agents evaluate differently — they need structured data and callable endpoints. Think of it as adding a new channel, not replacing the existing one. How long does this take? Agent Readiness Score: 48 hours. Strategy: a few weeks. Production-ready Agent Experience Layer: typically 90 days. You see results at each step. What if the agent landscape changes? It will. That's why we build on open protocols and structure your content to be platform-agnostic. The Operate phase exists for continuous monitoring as the landscape shifts. Why MING Labs and not a funded startup? This isn't a software problem — it's a transformation problem. Startups build tools. We go into your organization and build bespoke solutions on your existing infrastructure. 15 years, 50+ enterprises. Agents don't just show up as customers. They show up as colleagues too. [Hybrid Organisation](/hybrid-organisation) ## Start with what agents see today. Agent Readiness Score — by [Hyperize](https://hyperize.ai), a MING Labs venture. We test what AI says about you, where your tools are invisible, and where the door is already open. [Get your Agent Readiness Score](/score) Matthias or Sebastian respond personally. No sales team. No BDR. Step 1 ### Request Free. ~2 min form. Step 2 ### Snapshot Your score in 48 hours. Step 3 ### Full Report Detailed analysis across all three doors. Closing We test what AI says about you. Then we open the doors agents can already walk through. The agents are already here. Make sure they find the door. --- Canonical: https://www.minglabs.com/agent-experience Machine-readable index: https://www.minglabs.com/llms.txt