Automated quality assurance (Auto QA)
Automated quality assurance (Auto QA) uses AI to evaluate the quality of customer service interactions at scale — reviewing every conversation rather than the small sample (typically 2-5%) that manual QA processes can cover. Auto QA systems assess factors like accuracy, policy adherence, tone, resolution completeness, and customer effort.
Traditional QA in customer service has a fundamental sampling problem. Even dedicated QA teams can only review a fraction of interactions, which means most quality issues go undetected until they surface as customer complaints or CSAT drops. Auto QA eliminates this gap by scoring 100% of conversations — whether handled by human agents or AI.
Key capabilities of Auto QA systems include:
Policy adherence checking: Did the agent follow required procedures? Were mandatory disclosures made?
Accuracy verification: Was the information provided correct? Did the resolution match the customer's actual request?
Tone and empathy scoring: Was the interaction professional and appropriate for the situation?
Compliance flagging: Were regulatory requirements met? Were prohibited actions avoided?
Trend analysis: Surfacing systematic quality patterns across agents, teams, topics, or time periods
Auto QA is particularly valuable in two scenarios: (1) for human agent teams, where it replaces subjective, sample-based review with comprehensive, consistent evaluation, and (2) for AI agent deployments, where it provides continuous monitoring of AI behavior in production. In the second case, Auto QA acts as a safety net — catching issues that guardrails missed and providing the feedback loop needed to improve AI performance over time.
Related terms: quality assurance in customer service, AI observability, customer satisfaction score
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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.