> Bron: https://neuralex.nl/en/showcase/agent
> AI assistants search differently than humans. This scanner measures in one run how readable your site is for AI agents and delivers a concrete roadmap. Try it live.

Showcase · Agentic Search

# Get found by AI searching on behalf of people

AI assistants don't read banners — they read structure. This scanner measures in one run **how readable your site is for AI agents**, has a language model assess the content, and delivers a roadmap that provably works.

[Scan your site live](https://agent.neuralex.nl) [How the scanner works](#techniek)

Part of our website project: if you don't yet have a (modern) site, the [AI Agency](/en/showcase/ai-agency) builds you one — same project, different entry point.

15+

checks per scan

36 → 85+

score jump (case study)

19

AI agents served

Level 5

own reference site

From URL to roadmap

## Five steps, one report

01

### Enter a URL

The scanner fetches the site the way an AI assistant does — including the files agents look for that humans never see.

02

### 15+ checks in parallel

Technology, speed and AI readability are scanned simultaneously: llms.txt, schema.org, robots rules for AI agents, structure and content.

03

### AI reads your homepage

A language model assesses the content itself: is your proposition understandable to an agent searching on behalf of a customer? Where are the gaps?

04

### Score + roadmap

You get an AI-findability score with concrete priorities: what to fix first and what it delivers.

05

### From report to fix

Recipes are ready for the major platforms; via edge workers a site can be made agent-ready without rebuilding the existing stack.

Technology in detail

## Built by those who run it themselves

### The new discoverability

More and more visits come not from humans but from AI assistants searching on their behalf. Whoever is unreadable to agents soon won’t exist — this product makes that measurable.

### Measures what agents see

The scanner checks exactly what an AI agent encounters: llms.txt, schema.org data, agent-discovery records, robots rules for 19 known AI crawlers, and the machine-readability of the content itself.

### Proven on a real case

A webshop scored 36. After the recommended fixes via an edge worker — without changing a single line in the CMS — the score rose to 85+. The report is the playbook.

### Crash-resilient backend

The scanner runs as a native host process, deliberately outside the container stack. Heavy and async jobs (bulk scans, news crawls, reports) run via n8n workflows alongside it.

### Multi-LLM with failover

The AI analysis runs across a chain of providers with automatic failover and load spreading — model-agnostic, so it can also be EU-hosted or run fully on-prem.

### Own site as testing ground

The reference implementation runs on our own domains: Level 5 agent-ready, including agent discovery via DNS and a machine-readable service description. We sell what we run ourselves.

Built with Python / Flask (native)n8n orchestrationSQLiteEdge workersllms.txt · schema.orgAgent discovery (DNS)

See it for yourself

## Know where you stand within two minutes

Enter your URL and see your AI-findability score, the gaps found, and the first fixes right away. The scanner runs live — no waiting list.

[Open agent.neuralex.nl](https://agent.neuralex.nl) [Need help with the fixes?](/en/contact)

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Volledige (opgemaakte) versie: https://neuralex.nl/en/showcase/agent