Why teams compare Gradient Labs and Lorikeet: both are built for regulated industries, both run voice alongside chat and email, and both charge only for resolutions. The difference is scope. Gradient Labs markets to financial services and insurance. Lorikeet runs the same complexity across fintech and healthtech, with HIPAA coverage and published per-resolution pricing.
The Lorikeet difference:
Fintech and healthtech, not financial services alone - HIPAA coverage and a signed BAA where PHI is involved
Published pricing you can budget against, from 0.80 per resolution, rather than contact sales
Named helpdesk integrations out of the box - Intercom, Zendesk, Front and HubSpot
ISO 27001:2022 alongside SOC 2 Type II, and Coach reviews 100% of tickets
Trusted by CX leaders in fintech, health tech and complex industries
What is
?
Gradient Labs is a London-based AI customer operations platform for financial services, founded in 2023 by a team from Monzo. It sells named specialist agents for lending, disputes and KYB alongside voice and outbound, and positions around long-running work such as a 60-day dispute lifecycle or a KYC investigation. It publicly names customers including Wise, Monzo and Zego, and raised a Series A reaching $26m in September 2026.
What is Lorikeet?
Lorikeet is an agentic AI platform built for CX teams in complex, regulated industries. Unlike deflection-first tools, Lorikeet agents take real action processing refunds, updating customer records, booking appointments, and closing tickets end-to-end across voice, chat, email, and SMS. Teams get dedicated PM and engineering support, and pay only for resolutions they define as successful.
Lorikeet
vs
Gradient Labs
See how Lorikeet stacks up
10 questions to evaluate an agentic AI platform for CX
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.