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AI Technical Details

Adding AI Chat and AI Search to your website allows your users and customers to receive detailed and accurate answers to their queries with minimal cost and effort on your part. This solution provides an efficient way to improve customer experience, reduce support workload, and ensure 24/7 assistance.

We cut repetitive tickets by 73 % on our own support desk after deploying AI Chat and AI Search—slashing response times and freeing the team for high-value work, all without adding head-count.

Extra Wins

  • Real-time insight into top pain points & feature requests
  • Auto alerts that flag gaps in your docs so you can fix once, help everyone
  • Seamless live-agent hand-over (coming soon) for the few questions a bot shouldn’t handle
  • Fast ROI: setup in minutes, benefits show up almost immediately.
What is the cost of running AI Chat and AI Search features?
  • Account Setup: to use AI Chat and AI Search, set up an account and add credits with OpenAI
  • Cost Estimates:
      • low-traffic websites: Approximately a few dollars per month.
      • medium-traffic websites: Typically less than $10 per month.
  • Free Features: AI Chat and AI Search are included in the free Echo Knowledge Base plugin.
  • Paid Features: advanced features, such as analytics, are available in paid bundles.

Each Part Explained:

  • Your Visitor/User (Green)
    • Anyone visiting your website who needs help or has questions.
  • AI Search Box (Blue)
    • Where visitors type questions in everyday language – like asking a friend. No need for specific keywords.
  • AI Chat Assistant (Blue)
    • An interactive chat window for back-and-forth conversations when visitors need more detailed help.
  • KB Plugin (Red)
    • makes it all work by:
      – Connecting your website to AI services
      – Processing and storing your content
      – Managing conversations and search history
  • AI Brain (OpenAI) (Purple)
    • The artificial intelligence and storage of AI training data
  • Your Knowledge Base Content (Yellow)
    • All your articles, pages, and FAQs stored in AI memory, ready to answer questions instantly.
Do You Need Help Setting Up Your AI Chat?

On this page, open our AI Chat in the bottom right corner to discuss these instructions with our AI Chat assistant! 

Understanding Your Knowledge Sources

Every organization accumulates knowledge in diverse formats – from internal documents (PDFs, XML/CSV data, spreadsheets, code repositories) to support emails/notes and existing help-center articles:

  • Website Knowledge Base (KB): Existing help articles, FAQs, and guides on your WordPress site (the user-facing content).

  • Support and Reference Materials: Support tickets or emails, technical notes, product manuals, data files, code docs, and even relevant third-party links. These contain detailed insights that may not all be published on the website.

By auditing and gathering these sources, you get a comprehensive pool of company knowledge.

Defining Roles: Website Knowledge Base vs. AI Vector Store

Even after centralizing the content, it’s wise to present it in two complementary forms, each with a clear role:

  • The Website Knowledge Base: This is a curated set of articles on your site that provides high-level guidance and answers to common questions. Think of it as the user-friendly handbook – it contains overall explanations, step-by-step instructions, and FAQs that customers can easily read and understand. The KB shouldn’t overwhelm users with every detail; instead it offers the essential information and steps to guide users through common tasks or issues.

  • The AI Vector Store: This is an AI-oriented knowledge repository holding detailed and unstructured information in vector-embeddings for semantic search. It acts as the AI’s brain. All those support notes, detailed technical docs, data tables, and code snippets are ingested into this store (after processing) so that the AI can retrieve fine-grained information when answering user queries. In essence, the vector store is a robust, centralized database of knowledge drawn from all your sources (product docs, tickets, user feedback, etc.) that serves as the foundation for AI analysis and Q&A.

By separating these roles, you minimize overlap between what lives on the public KB and what’s hidden in the AI’s index:

  • The KB articles cover the most common scenarios in a concise way (no need to duplicate lengthy technical text there).

  • The AI store holds the in-depth information. When users ask the AI for more detail or edge cases not on the site, it can draw from this rich repository to give an answer.

This way, users have two paths: a self-serve KB for quick answers and an AI assistant that can provide deeper insight on demand. They work in tandem: the knowledge base builds confidence with well-structured guidance, and the AI can fill in details or handle unique questions.

Maintain and Update the Content Regularly

  • Feeding your AI outdated or incorrect information can be worse than providing no information. Make sure that whenever a process changes or a new requirement emerges, you update both the public article and its hidden notes.

  • Treat the knowledge base as a living document. If you fail to do so, users may get frustrated by contradictory or old answers. Schedule periodic reviews of both visible articles and notes to keep them current. An AI is only as good as its knowledge base – if the knowledge base evolves with your business or organization, the AI will continue to give accurate answers.

Structure and Format for AI Consumption

  • The way you format your content can impact how well the AI understands and retrieves it. Use clear headings, subheadings, bullet points, and other structured formatting in both articles and notes. This not only helps human readers scan the article, but also aids the AI.
  • Semantic structure (like proper HTML headings or markdown) can improve the AI’s ability to find the relevant section of an article when a question is asked. For instance, having a section titled “Requirements” in your hidden notes, or an FAQ list in the support notes, means the AI can pinpoint that section when the query matches those contexts.
  • Avoid burying critical info in long paragraphs without structure – breaking them into lists or Q&A format can make retrieval more precise. 
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