Selvakumar Duraipandian

The Problem: 
WordPress outputs HTML that’s difficult for AI systems to parse accurately. Important content gets lost in markup, scripts, and styling.
The Solution: 
AgentMark provides clean Markdown versions of your posts and pages through simple <code>.md</code> endpoints, plus an industry-standard <code>llms.txt</code> file that helps AI agents discover your best content.
<h4>Use Cases</h4>
<ul>
<li>AI Search Engines: Help tools like Perplexity, Claude, and ChatGPT cite your content accurately</li>
<li>RAG Systems: Enable companies to build knowledge bases from your public content</li>
<li>Documentation: Provide developers with clean, parseable API docs</li>
<li>Content Syndication: Share articles in a universal, lightweight format</li>
<li>Knowledge Graphs: Help semantic web tools understand your site structure</li>
</ul>
<h4>Key Features</h4>
<ul>
<li>Zero Configuration: Works out of the box with sensible defaults</li>
<li>Markdown Endpoints: Access any post/page as Markdown by adding <code>.md</code> to the URL</li>
<li>llms.txt Standard: Auto-generates discovery file for AI agents</li>
<li>YAML Front Matter: Rich metadata for better AI understanding</li>
<li>Flexible: Control which post types are exposed</li>
<li>Performance: Built-in caching and rate limiting</li>
<li>Privacy-Focused: Per-post control over AI access</li>
<li>Standards-Compliant: Follows emerging llms.txt specification</li>
</ul>
<h4>Business Value</h4>
<ul>
<li>Future-Proof: Position your content for the AI-driven web</li>
<li>Zero Cost: No API fees or external dependencies</li>
<li>SEO Boost: Alternate content formats can improve discoverability</li>
<li>Competitive Edge: Early adoption of AI-friendly formats</li>
<li>Analytics: Track which content AI agents prefer</li>
</ul>

AgentMark

AI-Ready Markdown Endpoints & llms.txt discovery for WordPress. Clean, machine-readable content for AI agents and RAG systems.

Muhammad Adnan Hanif

Fast RAGbot is an intelligent chatbot that uses Retrieval-Augmented Generation (RAG) with support for multiple AI providers to provide accurate answers based exclusively on your website content.
Key Features:
<ul>
<li>Multi-LLM Support: Choose between Gemini, OpenAI (ChatGPT), or Claude</li>
<li>Multi-Domain Indexing: Index up to 3 different domains</li>
<li>Document Upload: Bulk upload PDF, DOCX, PPTX, XLSX, TXT, XML, CSV</li>
<li>Conversation Memory: Maintains last 5 Q&A turns per session</li>
<li>Smart Follow-ups: Suggests questions when answer not found</li>
<li>Widget Customization: Custom colors, logo, position, theme CSS</li>
<li>Pre-chat Form: Optional name/email collection</li>
<li>Chat Logs: Full conversation logging with CSV export</li>
<li>Shortcode Support: Embed chat anywhere with <code>[ragbot_chat]</code></li>
<li>Grounded Responses: Answers only from your content – no hallucinations</li>
<li>Source Citations: Provides URLs of source pages for transparency</li>
<li>Mobile Responsive: Works perfectly on all devices</li>
<li>Security First: Rate limiting, nonces, and proper sanitization</li>
</ul>
How It Works:
<ol>
<li>Crawls and indexes your website content</li>
<li>Creates semantic embeddings using Google Gemini</li>
<li>Retrieves relevant content based on user questions</li>
<li>Generates contextual answers with source citations</li>
<li>Displays responses in a floating chat widget</li>
</ol>
Perfect For:
<ul>
<li>Customer support automation</li>
<li>FAQ assistance</li>
<li>Product information queries</li>
<li>Company information lookup</li>
<li>Documentation assistance</li>
</ul>
<h3>External Services & Data Usage</h3>
This plugin connects to external AI services to provide chatbot functionality. Below is a detailed explanation of what data is transmitted and how it is used.
<h4>External Services Used</h4>
Google Gemini API (https://ai.google.dev/) 
* Used for: Text embeddings and AI text generation 
* Data sent: User questions, website content chunks, conversation history 
* Privacy Policy: https://policies.google.com/privacy 
* Terms of Service: https://policies.google.com/terms
OpenAI API (https://openai.com/) – Optional 
* Used for: Text embeddings and AI text generation (when selected as active model) 
* Data sent: User questions, website content chunks, conversation history 
* Privacy Policy: https://openai.com/privacy/ 
* Terms of Service: https://openai.com/terms/
Claude API by Anthropic (https://anthropic.com/) – Optional 
* Used for: Text embeddings and AI text generation (when selected as active model) 
* Data sent: User questions, website content chunks, conversation history 
* Privacy Policy: https://www.anthropic.com/privacy 
* Terms of Service: https://www.anthropic.com/legal/terms
<h4>What Data Is Transmitted</h4>
<ol>
<li>User’s Question: The text message submitted by the website visitor</li>
<li>Retrieved Document Chunks: Relevant excerpts from your indexed website content (typically 5-8 chunks of ~1000 characters each)</li>
<li>Conversation History: Last 5 question-answer pairs from the current session</li>
<li>Model Parameters: Temperature (0.1), max tokens (1000), and other generation settings</li>
</ol>
<h4>Data Usage & Storage</h4>
<ul>
<li>Data is transmitted only for generating responses to user questions</li>
<li>No data is stored or used for training by external AI providers (per their API terms)</li>
<li>Data transmission occurs in real-time and is not cached by the plugin on external servers</li>
<li>All API communications use HTTPS encryption</li>
</ul>
<h4>Local WordPress Storage</h4>
The plugin stores the following data in your WordPress database:
Options (wp_options table): 
* <code>ragbot_settings</code> – Plugin configuration including API keys, widget settings, and preferences
Custom Tables: 
* <code>wp_rag_docs</code> – Indexed website pages and uploaded documents 
* <code>wp_rag_chunks</code> – Text chunks created from indexed content 
* <code>wp_rag_embeddings</code> – Vector embeddings for semantic search 
* <code>wp_rag_sources</code> – Content source configurations (domains, settings) 
* <code>wp_rag_logs</code> – Chat conversation logs (optional, includes user name/email if pre-chat form enabled) 
* <code>wp_rag_url_queue</code> – Queue of URLs pending indexing
Session Data: 
* PHP sessions store temporary conversation history (cleared when session ends) 
* Browser sessionStorage stores chat UI state (cleared when tab closes)
<h4>Data Control & Privacy</h4>
User Control: 
* Delete API keys anytime from Settings > Fast RAGbot > Models tab 
* Clear all indexed content using “Clear Index” button 
* Reset plugin settings to defaults 
* Export or delete chat logs from Settings > Fast RAGbot > Chat Logs tab
Data Deletion: 
* Deactivating the plugin preserves your data 
* Uninstalling the plugin removes all database tables and options 
* Use “Clear Index” to remove indexed content without uninstalling
Privacy Compliance: 
* No data is shared with third parties except your chosen AI provider 
* Chat logs are optional and stored locally in your database 
* Pre-chat form (name/email collection) is optional and disabled by default 
* All user inputs are sanitized and validated 
* Rate limiting prevents abuse (10 requests per 60 seconds per IP)
<h4>Developer Privacy Policy</h4>
For questions about data handling, please review: 
* Your chosen AI provider’s privacy policy (links above) 
* Your own website’s privacy policy (you are the data controller) 
* WordPress.org privacy guidelines: https://wordpress.org/about/privacy/
<h3>Privacy Policy</h3>
This plugin acts as a data processor, sending user questions to your chosen AI provider. You (the site owner) are the data controller and responsible for: 
* Disclosing AI service usage in your privacy policy 
* Obtaining user consent where required by law (GDPR, CCPA, etc.) 
* Ensuring compliance with local privacy regulations
The plugin stores chat logs locally in your database. If you enable the pre-chat form, user names and emails are stored and should be disclosed in your privacy policy.
<h3>Support</h3>
For support, please visit the plugin’s support forum or contact the developer.
<h3>Credits</h3>
<ul>
<li>Supports embeddings and text generation using Google Gemini, OpenAI, or Claude.</li>
<li>Built with WordPress coding standards</li>
<li>Follows accessibility best practices</li>
</ul>

Fast RAGbot

AI-powered chatbot with multi-LLM support (Gemini/OpenAI/Claude), multi-domain indexing, document upload, and conversation memory.

AgentMark vs Fast RAGbot