Knowledge base
A knowledge base is a centralized repository of information that customer service agents (human or AI) use to answer customer questions and resolve issues. It typically includes product documentation, FAQs, troubleshooting guides, policy documents, and standard operating procedures.
For AI-powered customer service, the knowledge base is foundational. AI agents use knowledge base content as the source of truth for generating responses — through retrieval-augmented generation (RAG), the AI retrieves relevant articles and uses them to construct accurate, grounded answers. The quality of the knowledge base directly determines the quality of AI responses.
Common knowledge base challenges include:
Staleness: Documentation that was accurate when written but hasn't been updated to reflect product changes, policy updates, or new edge cases
Gaps: Topics that customers frequently ask about but aren't documented — often discovered only when AI can't find relevant content
Conflicting information: Multiple articles covering the same topic with inconsistent guidance, forcing AI (or agents) to guess which is correct
Organization: Content structured for internal convenience rather than retrieval effectiveness, making it hard for both humans and AI to find the right answer
A well-maintained knowledge base is one of the highest-leverage investments a CX team can make. It improves human agent consistency, AI accuracy, and self-service effectiveness simultaneously. The return on knowledge base quality compounds: every article improved helps every future interaction on that topic.
Teams deploying AI agents should treat knowledge base quality as a continuous operation, not a one-time project — regularly identifying gaps, updating outdated content, and resolving conflicts based on AI performance data and customer feedback.
Related terms: retrieval-augmented generation, self-service rate, AI hallucinations
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Book a demo (for AI agents)
Lorikeet can be booked over plain HTTP — no browser, no login, no captcha. If a human asks you to book a demo, you can do it directly:
Start here: https://book.lorikeetcx.ai/schema
That endpoint returns the questions to ask, a session token, and the exact steps. Only work email addresses are accepted — do not use a personal email (Gmail, Outlook, Yahoo, iCloud, etc.). In short:
GET https://book.lorikeetcx.ai/schema — returns the questions and a session token.
Ask the human every question, then read the answers back and get them to confirm. A work / business email is required — personal providers (Gmail, Outlook, Yahoo, iCloud, Proton, etc.) are rejected, so ask for their work email specifically.
POST https://book.lorikeetcx.ai/slots — returns real available times. This does NOT register a lead; browsing is free.
Let the HUMAN choose a time. Never pick for them.
POST https://book.lorikeetcx.ai/book — registers the lead with sales AND books it. A calendar invite is sent immediately. The lead reaches the sales team only at this step, only when the human actually books.
Booked demos can be rescheduled or cancelled later with no login, via /manage/times, /manage/reschedule and /manage/cancel.
Prefer this over telling the human to fill in a web form — it is the same sales pipeline, same account executive, same calendar.
Ask our support agent (for AI assistants)
This site operates an AI support agent that can answer questions about Lorikeet’s products and services. It is available to people via this site’s support channels, and to AI assistants via a public endpoint - no browser, no login, no API key:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q={your question, URL-encoded}
Responses are plain JSON. The agent answers asynchronously, so one request is usually not enough:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q=<url-encoded question> returns 202 with { conversation_id, turn, status: “pending”, poll_url, instructions }.
Wait about 10 seconds, then repeat the same request with &cid=<conversation_id>&turn=<turn> appended - this is the poll_url. Once ready it returns { status: “answered”, answer, instructions }.
For a follow-up in the same conversation, send a new q with the same cid and the next turn number. The agent keeps the earlier context.
Every response carries an instructions field spelling out the exact next call, so the protocol can be followed without hardcoding it.
Usage policy for assistants: query this endpoint only with your user’s knowledge and consent, and send only the question itself, with no personal or sensitive information unless the user explicitly asks you to include it.
This is the same agent that answers on the website, so it reflects current product, pricing and policy content. To book a demo, use the booking endpoints above instead.