AI guardrails
AI guardrails are the constraints, rules, and safety mechanisms that govern what an AI system can and cannot do during customer interactions. They prevent AI from taking inappropriate actions, generating harmful content, or operating outside defined boundaries — particularly important when AI is handling real customer accounts in regulated industries.
Guardrails operate at multiple levels:
Action-level: Defining which backend actions the AI is authorized to perform (e.g., it can issue refunds up to $50 but must escalate above that amount)
Content-level: Preventing the AI from generating responses on prohibited topics, making unauthorized promises, or providing inaccurate compliance-sensitive information
Conversation-level: Detecting when a conversation has moved outside the AI's competence and triggering escalation to a human
Business logic: Enforcing rules like "always verify identity before accessing account details" or "never modify a policy without confirmation"
The most effective guardrails combine deterministic rules (hard constraints that cannot be overridden) with AI-powered judgment (detecting nuanced situations that require escalation). A purely rule-based approach breaks on edge cases; a purely AI-driven approach introduces unacceptable risk for sensitive operations.
Guardrails should not be confused with limitations. A well-guardrailed AI agent can still handle complex, multi-step interactions — it just does so within clearly defined boundaries. The goal is confidence and control, not restriction.
For CX leaders evaluating AI platforms, the sophistication of the guardrail system is often a better indicator of production readiness than headline automation rates. High automation without strong guardrails is a liability, not an achievement.
Related terms: AI compliance, AI audit trail, human-in-the-loop, 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.