Intent detection
Intent detection (also called intent recognition or intent classification) is the AI capability that identifies what a customer is trying to accomplish from their message. When a customer writes "I haven't received my package and it's been two weeks," the intent detection system classifies this as a shipping/delivery inquiry, distinguishing it from a return request, a billing question, or a product complaint.
Intent detection is the first step in any AI-powered customer service interaction. The accuracy of intent detection directly determines whether the AI can route the conversation correctly, retrieve relevant information, and take appropriate actions.
Modern intent detection has moved beyond keyword matching and simple classification. Large language models can:
Detect multiple intents in a single message ("I need to return this item AND update my shipping address")
Handle implicit intent where the customer doesn't state their goal directly ("This is the third time I've been charged twice" implies a refund request and a systematic billing issue)
Distinguish intent from emotion (a frustrated customer asking about a return vs. a neutral customer asking the same thing may need different handling)
Recognize intent shifts mid-conversation as the customer's needs evolve
For CX teams, intent detection quality is a leading indicator of overall AI performance. If the AI frequently misidentifies what customers want, everything downstream fails — wrong knowledge articles are retrieved, wrong actions are taken, and customers are sent down incorrect conversation paths.
Evaluating intent detection requires looking beyond top-line accuracy rates. A system that correctly identifies 95% of intents might still fail badly on the 5% it misses — particularly if those misses cluster in high-value or sensitive categories.
Related terms: natural language processing, sentiment analysis, conversational AI
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.