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<p>Similo uses AI embeddings to find and display semantically related posts — articles that are actually about the same topic, even if they don’t share tags or categories.</p>
<p>Built for professional blogs with hundreds of posts: law firms, consultancies, academic publishers, and anyone whose readers deserve better content discovery.</p>
<p><strong>How it works</strong></p>
<ul>
<li>When a post is published, Similo generates an AI embedding of its content</li>
<li>When a reader views a post, Similo compares embeddings to find the most similar articles</li>
<li>The most relevant posts are displayed as “Further Reading” at the bottom of each article</li>
</ul>
<p><strong>Why it’s different</strong></p>
<p>Most related post plugins match by tags or categories. Similo understands meaning — so a post about GDPR enforcement and a post about data privacy fines will be connected, even if they were never tagged the same way.</p>
<p><strong>Requirements</strong></p>
<ul>
<li>No API key needed — embeddings are handled via Similo’s external service.</li>
</ul>
<h3>External Services</h3>
<p>This plugin sends post content to an external server to generate AI embeddings for related post detection.</p>
<p><strong>What data is sent:</strong> Post title and content (text only)<br />
<strong>When:</strong> When a post is published or updated<br />
<strong>Service:</strong> lecto-server.fly.dev</p>
<ul>
<li><a href="https://lecto-server.fly.dev/terms" rel="nofollow ugc">Terms of Service</a></li>
<li><a href="https://lecto-server.fly.dev/privacy" rel="nofollow ugc">Privacy Policy</a></li>
</ul>


Similo: AI Related Posts

AI-powered related posts for content-heavy WordPress blogs. Connects articles by meaning, not just tags.

krunalb18

<p>VecPost AI Search for Posts replaces WordPress’s default SQL LIKE search with vector-based semantic search. Instead of matching exact words, it understands the <em>meaning</em> of a search query.</p>
<p><strong>Example:</strong> A user searching “heart workouts” will find your post titled “Best cardiovascular exercises” – even though no words overlap – because the meanings are similar.</p>
<h4>How It Works</h4>
<ol>
<li>When you publish a post, the plugin sends its content to your chosen AI provider (OpenAI or Google Gemini) to generate a vector embedding – a list of numbers that represents the meaning of the text.</li>
<li>These numbers are stored in your database.</li>
<li>When a user searches, their query is also converted to numbers, and the plugin finds posts whose numbers are closest – meaning most semantically similar.</li>
</ol>
<h4>Features</h4>
<ul>
<li>Semantic search powered by OpenAI (<code>text-embedding-3-small</code> or <code>text-embedding-3-large</code>) or Google Gemini (<code>gemini-embedding-001</code>)</li>
<li>Hybrid re-ranking: combines semantic similarity with keyword matching for best results</li>
<li>Gutenberg block and shortcode <code>[vecpost_semantic_search]</code> for easy placement</li>
<li>Bulk indexer with progress bar for existing posts</li>
<li>WP-CLI support: <code>wp vecpost-semantic-search index</code>, <code>wp vecpost-semantic-search status</code>, <code>wp vecpost-semantic-search search "query"</code></li>
<li>Configurable scoring thresholds via Settings -> VecPost – AI Semantic Search for Posts</li>
<li>Automatic re-indexing when you switch embedding models</li>
<li>Results cached via WordPress object cache (Redis/Memcached compatible)</li>
</ul>
<h4>Third-Party Services</h4>
<p>This plugin sends post content to external AI APIs to generate embeddings. By using this plugin, you agree to the terms of service and privacy policies of your chosen provider:</p>
<ul>
<li><strong>OpenAI:</strong> https://openai.com/policies/privacy-policy | https://openai.com/policies/terms-of-use</li>
<li><strong>Google Gemini:</strong> https://policies.google.com/privacy | https://ai.google.dev/terms</li>
</ul>
<p>No data is sent without your API key being configured. Data is only transmitted when posts are published or during bulk indexing.</p>
<h4>Performance Note</h4>
<p>Semantic search requires loading all embeddings into PHP memory for comparison. This works well for sites with up to approximately 1,500 posts. For larger sites, a dedicated vector database (pgvector, Qdrant, or Pinecone) is recommended.</p>


VecPost AI Search for Posts

AI-powered semantic search for WordPress posts. Understands meaning, not just keywords. Powered by OpenAI or Google Gemini.

Similo: AI Related Posts vs VecPost AI Search for Posts