Lorikeet
AI-powered customer service agent that follows SOPs to resolve complex issues across chat, email, and voice channels
Visit Website ↗What is Lorikeet
Lorikeet is an AI customer service platform developed by an Australian team, which has raised approximately $75 million in just 10 months. It stands out in the crowded customer service automation space with a clear positioning: instead of being just a chatbot that answers questions, Lorikeet aims to be a concierge that handles complex cases like a human customer service agent. It operates across chat, email, and voice channels, making judgments and taking actual actions by calling backend systems, rather than just providing answers.
Lorikeet uses a graph-based design approach, allowing you to create a controllable workflow for your customer service SOPs. The AI decides the next step at each node based on predefined rules. With customers spanning the US, Europe, and Australia, including unicorns like Airwallex, Linktree, Flex, and Eucalyptus, Lorikeet has gained significant traction in industries like fintech and healthcare, where processes are complex and the cost of errors is high.
Key Features and Use Cases
Priced on a "pay-per-resolved-ticket" model, Lorikeet's official website shows a starting price of around $500 per month, positioning it as a mid-to-high-end solution. Compared to competitors that emphasize "natural language description" for quick deployment, Lorikeet's selling point is its controllability and predictability. You can precisely design workflows, limiting AI actions within a framework, which is particularly attractive to financial and medical customer service teams that cannot tolerate AI errors. However, this comes at the cost of requiring more effort to design the workflows during the onboarding process, making it less suitable for simple question-answering needs.
Key Features
- Graph-based design for controllable customer service workflows
- Multi-channel support across chat, email, and voice
- Ability to call backend systems for actual actions
- Judgment-based decision-making rather than just answering questions
- Pay-per-resolved-ticket pricing model
Pros
- Controllable workflows suitable for high-risk industries
- Ability to handle complex tickets and actual operations
- Validation from multiple unicorn customers
Cons
- Starting price of around $500 per month, with a relatively high threshold
- Requires effort to design workflows during onboarding
- Overly complex for simple needs
Use Cases
- Complex customer service case handling for fintech companies
- Compliant customer service for the healthcare industry
- Automation of tickets requiring multiple backend system integrations
- Omnichannel support across chat, email, and voice
Editor's Note
Editor's note: Lorikeet's graph-based, controllable design approach directly addresses the pain point of financial and medical customer service teams that are hesitant to let AI handle cases without control. With a strong customer list, I give it a 4.2 rating. However, its non-lightweight approach may deter those looking for an easy, out-of-the-box solution.
FAQ
How does Lorikeet differ from regular chatbots?
Lorikeet not only answers questions but also follows human customer service SOPs to make judgments and take actions by calling backend systems, positioning itself as a concierge for complex case resolution.
How does Lorikeet charge its customers?
Lorikeet follows a pay-per-resolved-ticket pricing model, with a starting price of around $500 per month, as shown on its official website. This positions it as a mid-to-high-end solution suitable for teams with sufficient ticket volume and complexity.