Warm handoff
A warm handoff (also called a warm transfer) is the process of transferring a customer from one agent (or from an AI agent to a human agent) while preserving the full context of the conversation — so the customer doesn't have to repeat their issue. The receiving agent sees the conversation history, understands what's already been attempted, and picks up where the previous interaction left off.
This is in contrast to a cold handoff, where the customer is transferred without context and must re-explain their situation. Cold handoffs are consistently rated as one of the top customer frustrations in service interactions.
In AI-to-human handoffs, warm handoff quality is critical because it occurs at the moment of highest customer sensitivity. The customer has already interacted with AI — possibly for several turns — and the escalation to a human typically happens because the issue is complex, the customer is frustrated, or the AI reached its limits. Starting over at this point compounds the frustration.
An effective warm handoff includes:
Full conversation transcript: Everything the customer has said and the AI has responded
Issue summary: A concise description of the customer's problem and what's been attempted
Customer context: Account details, history, sentiment indicators
Reason for escalation: Why the AI couldn't handle the interaction, helping the human agent approach it appropriately
Attempted actions: What the AI already tried, so the human agent doesn't repeat steps
For CX teams evaluating AI platforms, testing the handoff experience is essential. The smoothness of the handoff — from the customer's perspective — is often more important than the AI's resolution rate, because it determines the experience for every customer who needs human help.
Related terms: escalation rate, human-in-the-loop, customer effort score
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.