Compliance automation
Compliance automation uses AI and rules-based systems to enforce regulatory requirements within customer service interactions — ensuring that mandatory disclosures are delivered, prohibited actions are prevented, required verifications are performed, and interaction records meet regulatory standards, all without depending on individual agent knowledge or memory.
In regulated industries, compliance failures in customer service create real liability:
Financial services: Failing to disclose fees, providing unsuitable product advice, or processing unauthorized transactions
Healthcare: Sharing medical information without proper consent, providing clinical advice outside scope, or violating HIPAA data handling requirements
Insurance: Misrepresenting coverage, failing to deliver mandatory disclosures, or improperly handling claims
Traditional compliance in customer service relies on agent training and manual QA — both of which are inherently limited. Agents forget procedures under pressure, new hires make mistakes, and QA sampling catches only a fraction of violations.
AI-powered compliance automation can:
Enforce disclosure requirements: Automatically including required language in relevant interactions
Block prohibited actions: Preventing the AI (or flagging for human agents) actions that violate regulatory rules
Verify identity: Ensuring proper authentication before accessing sensitive information
Maintain records: Creating audit-ready logs of every compliance-relevant decision and action
Monitor continuously: Reviewing 100% of interactions for compliance violations, not just a sample
For CX leaders in regulated industries, compliance automation isn't just an efficiency tool — it's a risk management strategy. The cost of a compliance violation (fines, litigation, reputational damage) dwarfs the cost of implementing automated controls. Compliance should be a primary evaluation criterion when selecting AI customer service platforms, not an afterthought.
Related terms: AI compliance, AI audit trail, AI guardrails, automated quality assurance
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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.