Let's be honest, customer support has gotten complicated. We're long past the days of basic chatbots that could only serve up links to FAQ articles. The new wave of AI agents is much smarter, and they’re starting to tackle the multi-step problems that used to require a human touch.
Lorikeet AI is one of the bigger names in this space, branding itself as a "universal AI concierge" that can handle high-stakes customer issues. It sounds pretty impressive, and for certain types of companies, it might just be the ticket.
But is it right for your team? My goal here is to give you a straightforward and detailed Lorikeet AI review. We'll get into how its technology works, what it’s good at, and where it might fall short. We'll cover its features, the setup process, and the pricing so you can get a clear picture of whether it fits your needs. We'll also look at some alternatives for teams who need a bit more flexibility and speed.
What is Lorikeet AI?
So, what exactly is Lorikeet AI? In short, it’s an AI support agent built to resolve complex customer problems, not just deflect them. It’s aimed squarely at companies in tricky, regulated industries like fintech and healthtech, where getting things right is non-negotiable.
Lorikeet's Intelligent Graph Orchestration.Its main claim to fame is that it doesn't just find a help article; it actually follows your company's internal Standard Operating Procedures (SOPs) to solve an issue from start to finish. Think of it less like a knowledge base search tool and more like a very diligent junior agent who follows the playbook to the letter, every single time.
Lorikeet claims it can handle tasks that would make a simple bot crash, like replacing a lost credit card, changing a flight, or processing a payment. The entire system is focused on those tougher Tier 2 and Tier 3 tickets that eat up so much of your team's day. They achieve this with something they call an "Intelligent Graph architecture," which is a fancy way of saying they use a very structured, rule-based system to prevent the kind of random mistakes or "hallucinations" you sometimes see with general AI.
How Lorikeet AI works
Let’s get into the nuts and bolts of how Lorikeet AI handles support tickets. This is where you can see both its biggest strengths and its most significant limitations.
Following complex, multi-step workflows
Lorikeet is at its best when it's executing rigid, pre-defined workflows. If your company has meticulously documented, step-by-step processes for every common issue, Lorikeet is built to shine. It hooks into your internal systems and follows a script perfectly, making decisions based on a clear set of if-then rules.
For example, a standard refund request might be a simple decision tree: a customer asks for a refund, the AI checks if it’s within the 30-day window, verifies the order in a tool like Stripe, confirms the item was returned, and then triggers the refund.
A flowchart from a Lorikeet AI review showing a refund process.For industries where compliance is everything, this level of consistency is fantastic. But this approach has one major catch: it assumes all your processes are, and always will be, perfectly mapped out. What happens when a customer has a unique problem that doesn’t fit into a neat little box? Or what if the solution isn't in a formal workflow but hidden in an old support ticket, a Confluence page, or a messy Google Doc? This is where a workflow-only system can get brittle and just end up escalating anything it doesn’t recognize, which kind of defeats the purpose.
Where rigid workflows fall short
The truth for most support teams is that knowledge is messy. A huge amount of your team’s expertise isn't in a pristine SOP document; it’s scattered across thousands of past conversations in platforms like Zendesk or Intercom. Your best agents solve tricky new problems by remembering how they handled something similar months ago.
This is where a more adaptable AI is needed. While structured workflows have their place, a truly smart AI should be able to learn from all of your company’s knowledge, structured or not.
This is the approach taken by platforms like eesel AI, which learns directly from your historical support tickets and existing knowledge bases. It can pick up on nuance, adopt your brand’s tone, and find solutions to problems that have never been written down in a formal process. It delivers accurate answers without making you build a complicated flowchart for every possible question a customer might ask.
This screenshot shows how eesel AI connects to various knowledge sources, such as Zendesk, Intercom, and Google Docs, to train its AI. This visual supports the point made in this Lorikeet AI review about adaptable AI learning from scattered knowledge.The setup process: What to expect
A powerful tool is only useful if you can actually get it up and running. So, what does it take to implement Lorikeet AI, and how much say do you have in how it works?
Integrating with your tools
Lorikeet says it integrates with essential platforms like Zendesk, Stripe, and Shopify. That’s good news, because it means the AI can pull data and take action in your team’s existing tools without forcing you to switch systems.
That said, the website is surprisingly quiet about the details of the implementation. They even mention on their blog that competitors can take 6-12 months to launch, which strongly hints that their own setup isn't a walk in the park. There’s no talk of a self-serve option, so you’re likely looking at a lengthy onboarding process that requires a lot of time from both their engineers and yours.
The problem with a "black box" setup
When you can't set up a tool yourself, you run into a few problems. You become completely reliant on their professional services team for the initial setup and for any changes you want to make down the road. This can be a slow and expensive way to work, especially if your team likes to move fast.
Even more concerning is the lack of any mention of a way to test or simulate the AI’s performance before you let it talk to customers. This "launch and hope for the best" approach is a huge gamble for your brand. You’re essentially crossing your fingers that it works as promised, which is a pretty scary thought.
This is a big difference from more modern, self-serve platforms. With eesel AI, for instance, you can connect your helpdesk and knowledge bases in a few clicks and be ready to go in minutes, not months. Crucially, eesel AI includes a simulation mode that lets you test the AI on thousands of your actual past tickets. You get a clear forecast of its resolution rate and can review exactly how it would have replied, letting you tweak its behavior in a safe sandbox. This gives you total control and confidence before you automate a single customer email.
This image from our Lorikeet AI review displays eesel AI's simulation mode, where users can test the AI's performance on past tickets before going live.This video features an interview with Steve Hind, the co-founder of Lorikeet AI, discussing the journey of building the company.
Breaking down the pricing
Cost is always a huge piece of the puzzle. Let’s take a look at Lorikeet's pricing and what it really means for your budget.
The pricing model
To their credit, Lorikeet's pricing is public. Their entry-level "Start" plan is $500 per month. Here’s what you get for that:
| Plan Tier | Monthly Price | Resolutions Included | Key Features |
|---|---|---|---|
| Start | $500 / month | Up to 750 resolutions | Email & chat support, 1 brand, 5 editor seats |
The system runs on credits. You get a certain number of credits each month, and every time the AI resolves a ticket, it uses some of them up. According to their site, simple FAQ answers use fewer credits than complex resolutions that involve multiple steps.
The issue with per-resolution pricing
While the transparency is nice, a per-resolution pricing model comes with some serious hidden downsides. First off, it means your automation bill grows right alongside your ticket volume. As your business gets bigger and you get more customer inquiries, your AI costs go up. You’re effectively penalized for being successful.
This model also makes your expenses unpredictable. A month with a small product bug, a viral marketing post, or just a seasonal rush could cause your ticket volume to spike, leaving you with a surprisingly large bill. Budgeting becomes a guessing game, which is the last thing anyone wants.
This is where it pays to look at other options. For example, eesel AI's pricing is built for predictability. Plans are based on a flat monthly fee for a generous number of AI interactions (which includes both replies and actions taken), not how many tickets are resolved. You know exactly what you’ll pay every month. With plans that start at a more accessible price and offer flexible month-to-month billing, it’s a much more scalable and budget-friendly way to get started with automation.
This screenshot of eesel AI's pricing page, included for this Lorikeet AI review, highlights a predictable, flat-fee model as a scalable alternative.Is Lorikeet AI right for you?
So, after this Lorikeet AI review, what's the final word? It's clear that Lorikeet is a powerful tool with a very specific customer in mind. It seems best suited for enterprise companies that have big budgets, extremely rigid internal processes, and the patience for a long and involved implementation. If you’re a large fintech or healthtech company with perfectly documented workflows, its SOP-driven model could be a great way to ensure accuracy and compliance.
For most other teams, however, the drawbacks are pretty significant. The likely long setup time, the lack of a self-serve option, and the unpredictable pricing model make it a tough sell. And without a way to simulate performance before going live, you’re taking on a lot of unnecessary risk.
If your team needs a solution that’s fast, easy to manage, and affordable, you'll probably want to look elsewhere. You shouldn't have to wait months or spend a fortune to start benefiting from AI.
If you’re looking for an AI support agent you can set up yourself in a few minutes, test thoroughly, and pay for with a predictable subscription, you might want to check out eesel AI. You can connect all your knowledge sources, instantly see how it would perform on your real historical data, and start automating support today.
Frequently asked questions
Lorikeet AI is primarily designed for enterprise companies in highly regulated industries like fintech and healthtech. It's best for organizations with large budgets and extremely rigid, perfectly documented Standard Operating Procedures (SOPs).
The "Intelligent Graph architecture" relies on a structured, rule-based system to follow pre-defined workflows and SOPs precisely. This approach minimizes "hallucinations" and ensures compliance, but it struggles with problems outside its strict rules.
Expect a lengthy and involved implementation process that requires significant time from both Lorikeet's engineers and your own team. The review suggests there's no self-serve option, leading to reliance on their professional services for setup and changes.
No, the review highlights that Lorikeet AI's rigid workflow system struggles with unique problems not fitting into neat, pre-mapped processes. It's built to follow scripts precisely, meaning anything outside those scripts might get escalated rather than resolved.
The per-resolution pricing model means your automation costs increase directly with your ticket volume, potentially penalizing business growth. It also makes budgeting unpredictable, as seasonal rushes or unexpected issues can lead to surprisingly high bills.
Yes, the review mentions platforms like eesel AI as more adaptable alternatives. These are designed for self-serve setup in minutes, learn from all historical knowledge (structured or not), and offer predictable flat-fee pricing.
This review suggests Lorikeet AI is most appropriate for large organizations with substantial resources, a high need for compliance, and an existing infrastructure of meticulously documented, multi-step internal processes. For most other teams, its rigid structure and setup time might be limiting.
