AI OPTIMIZATION

Intelligent Content Transformation

Our AI engine rewrites your pages as enriched markdown -- Schema.org metadata, FAQs, entity definitions, and semantic context, in the format LLMs tokenize best. AI systems don't just crawl your site, they understand it.

Start OptimizingSee all features

Key metrics

12x EnrichmentMarkdown Output16K Token LimitEdge-CachedSub-50ms Cached

How AI optimization transforms your content

The AI pipeline identifies what's missing and fills the gaps automatically.

Feature 01

Content Gap Analysis -- AI-Powered Enrichment

Before (origin HTML · thin content)

<div class="product-page">
  <h1>Running Shoes</h1>
  <p>Great shoes for running.</p>
  <div class="price">$149.99</div>
  <button>Add to Cart</button>
</div>

<!-- ~200 tokens. No schema,
     no FAQs, no context. -->

After (enriched markdown)

---
title: Running Shoes
schema:
  type: Product
  price: 149.99
  rating: { value: 4.7 }
---

# Running Shoes

Running shoes are specialised
footwear designed for forward
motion, with cushioned midsoles
and breathable uppers...

## Specifications
| Feature | Detail   |
|---------|----------|
| Midsole | EVA foam |
| Drop    | 10mm     |

## FAQ (14 questions)
- Are these good for trail running?
- What sizes are available?
- How do they compare to Ultra Boost?
- ... + 11 more

## See also
- [Trail running shoes]
- [Marathon-grade footwear]

# ~2,400 tokens · 12x enriched

Our AI engine analyzes your page content with deterministic settings to identify what's missing for AI systems to truly understand your content. The content gap analyzer then rewrites the page as an enriched markdown document with schema metadata, FAQs, and entity context baked in -- served only to AI crawlers, never to human visitors.

Enrichments injected

  • Schema.org LD+JSON structured data (Product, Article, FAQ, etc.)
  • FAQ sections with 10-15 AI-generated questions and answers
  • Entity expansions with Wikipedia-style definitions
  • Semantic relationship mapping (alternatives, related items)
  • "What is X?" contextual paragraphs for disambiguation
  • Credibility markers and factual statistics

Transformation pipeline

Crawler Detected

GPTBot / ClaudeBot / PerplexityBot

Content Fetched

Origin HTML retrieved

Gap Analysis

AI identifies missing enrichments

Rewritten as Markdown

Enriched .md with schema + FAQs + context → edge cache

Feature 02

Content Rules -- Per-Path Configuration

Content rules let you fine-tune AI optimization on a per-path basis. Set custom AI prompts for different sections of your site, configure cache TTLs, scope rules to specific domains, and control exactly how the AI transforms each page type.

Configuration options

  • Path Patterns -- Match URLs with glob patterns like /products/* or /blog/**
  • Custom AI Prompts -- Tell the AI exactly how to enrich specific content types
  • Cache TTL -- Configure per-rule caching from 5 minutes to 30 days (default 1h)
  • Domain Scoping -- Apply rules to specific domains or tenant-wide

Content rule configuration

{
  "name": "Product Pages",
  "path_pattern": "/products/*",
  "domain_id": "d_abc123",
  "is_active": true,
  "custom_prompt": "Focus on product specs,
    pricing comparisons, and buyer FAQs.
    Add Schema.org Product markup with
    offers, ratings, and availability.",
  "cache_ttl": 3600,
  "priority": 10
}

AI model parameters

Model:       Large-scale instruction-tuned LLM
Temperature: 0.4 (deterministic)
Max Tokens:  4,000
Pipeline:    Content Gap Analyzer
Cache:       Edge-cached (configurable TTL)
Fallback:    Secondary AI provider (auto-failover)

Crawler-only activation

AI optimization only activates for recognized AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Anthropic-AI, Google-Extended, etc.). Human visitors always receive the original, unmodified page. Zero impact on user experience.

HOW IT WORKS

Four steps to AI-optimized content

From crawler detection to enriched response -- fully automated at the edge.

Step 01

AI crawler detected

Wrenda identifies the incoming request as an AI crawler by matching user-agent patterns. GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and dozens more are recognized in under 1ms.

Step 02

Origin content fetched

The original HTML is fetched from your origin server. Static assets (images, CSS, JS) are automatically detected and skipped -- they pass through directly with CDN caching.

Step 03

AI analyzes content gaps

Our AI engine runs the content gap analyzer with deterministic settings. It identifies missing Schema.org markup, thin content sections, absent FAQs, and areas lacking semantic context.

Step 04

Enriched markdown served & cached

The enriched markdown document is served to the crawler with Content-Type: text/markdown and cached at the edge with a configurable TTL. Subsequent requests for the same URL serve from cache in single-digit milliseconds.

USE CASES

Optimized for every content type

AI optimization adapts to your content -- whether you sell products, publish articles, or host documentation.

E-Commerce Product Pages

Product pages get Schema.org Product markup with offers, ratings, and availability. AI-generated FAQs cover sizing, shipping, comparisons, and care instructions.

  • Schema.org Product + Offer + AggregateRating
  • Buyer FAQ sections (10-15 questions)
  • Competitor comparisons and alternatives

Publisher Articles

Articles are enriched with Article schema, entity definitions for key terms, topical context paragraphs, and comprehensive FAQ sections for featured snippet eligibility.

  • Schema.org Article + Author + DatePublished
  • Entity expansions for technical terms
  • Topical authority signals and citations

SaaS Documentation

Documentation pages receive TechArticle schema, code example annotations, API reference enrichments, and troubleshooting FAQs that AI assistants can surface directly.

  • Schema.org TechArticle + HowTo markup
  • API parameter and endpoint descriptions
  • Troubleshooting FAQs for common issues
LIVE EXAMPLE

See the enrichment in action

Send a request as GPTBot and see how Wrenda enriches the response automatically.

ai-optimization-demo.sh
# Request as GPTBot -- triggers AI optimization
curl https://yoursite.com/products/running-shoes \
  -H "User-Agent: GPTBot/1.0"

# Response headers show optimization was applied
HTTP/2 200
X-AI-Optimized: true
X-Crawler-Action: optimize
X-Content-Enrichment: 12.4x
X-Cache: HIT
Content-Type: text/markdown; charset=utf-8

# Same URL as a regular browser -- no optimization
curl https://yoursite.com/products/running-shoes \
  -H "User-Agent: Mozilla/5.0 Chrome/120"

# Response: original page, untouched
HTTP/2 200
X-Crawler-Action: pass-through
Content-Type: text/html; charset=utf-8

~200 → 2,400

Token enrichment (12x)

16K tokens

Per-page output limit

< 50ms

Cached response time

FAQ

AI Optimization FAQs

Common questions about how Wrenda transforms content for AI crawlers.

Wrenda matches the request User-Agent against a continuously-updated list of AI crawler patterns: GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, OAI-SearchBot, Google-Extended, Bytespider, CCBot, Applebot-Extended and more. Detection is per-request — the same URL can be served as enriched markdown to GPTBot and the original page to a regular browser.

Get Started

Make AI systems understand your content

Enable AI optimization in minutes. No code changes required -- just point your domain and let our AI engine do the rest.

Start Optimizing

14-day free trial -- No credit card required