Lorikeet exists to give every company the ability to deliver a universal concierge to their customers. Customers should demand better support, and Lorikeet's platform will solve their issues by knowing their context and taking actions for them, 24/7, via the channel of their choice.
Making this possible requires focusing on building an AI system that’s capable of providing high quality, human assistance. The industry standard approach of having the AI search help center materials on behalf of customers just won’t cut it.
Lorikeet has been focused since day one on building an AI support platform capable and trustworthy enough to manage complex conversations and take high-stakes actions, grounded by strict AI safety and operational guardrails. Rather than giving the AI open access to risky actions like canceling customer accounts, Lorikeet uses granular permissions and dynamic gating to enforce safe, auditable execution.
But inbound / reactive support is just the beginning. Lorikeet is enabling its customers to provide proactive, personalized engagement to their users, blurring the boundaries between support, lifecycle marketing, and traditional software experiences. With our customers we’re defining the new standard for customer experience.
We come from a wide range of global technology leaders and fast-paced startups
Lorikeet’s founders bring experience from the AI research frontier and from building power tools for operations teams. Steve led product teams at Stripe and Watershed, building tooling to enable complex processes like carbon accounting and financial reporting at scale.
Jamie was a research tech lead at Google Brain, leading research on factual grounding in large language models. He was the third named author on Google’s breakthrough 2022 LaMDA paper, and the fourth named author on the 2020 predecessor Meena paper.
Both love a good user experience, and love working to bring the research frontier of AI into the application layer.
Beyond the founders, Lorikeet is fortunate to be propelled by a stellar team, that spans Sydney, Australia and the US. The team boast world-class experience at Silicon Valley and Australian tech powerhouses like Stripe, Google, Salesforce, Dropbox, Atlassian, Canva, and Dovetail. Lorikeet knows first hand that diverse teams are higher performing and are proud that our team reflects a broad spectrum of identities and lived experiences.
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.