AI Agent Handoff
AI agent handoff is the process of transferring a customer conversation from an AI system to a human agent, including the passing of context, conversation history, and relevant customer information.
Handoff is where many AI implementations fail the customer. Poor handoffs dump customers to agents without context, forcing repetition of information already provided. Good handoffs transfer full conversation history, customer identification, issue classification, and attempted resolution—everything the agent needs to continue seamlessly.
Effective handoff design requires decisions about: when to handoff (confidence thresholds, explicit requests, escalation triggers, sensitive topics), where to route (skill-based routing, priority queuing, relationship preservation), and what to transfer (conversation transcript, classified intent, customer data, suggested resolution). The handoff itself should be invisible to the customer or explicitly acknowledged ("I'm connecting you with a specialist who can help further").
For support operations, handoff rate and handoff quality are critical metrics. High handoff rates suggest the AI can't handle common issues. Poor handoff quality (agents asking customers to repeat themselves) erodes trust in the overall system. The goal: AI resolves what it can, hands off smoothly when it can't, and sets agents up for success rather than creating frustration for customers and staff alike.
Related terms: Human-in-the-loop, AI agent orchestration, Intelligent Virtual Agent
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# CX Metrics & KPIs
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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.