Lorikeet AI review (2025): Features, pricing & a flexible alternative
Stevia Putri
Last edited September 22, 2025
AI for customer support is evolving at lightning speed. We’ve moved past those clunky, keyword-based chatbots and into an era of smart AI agents that can actually understand what a customer is saying, follow complex instructions, and solve real problems. It’s a pretty exciting time, with the promise of freeing up support teams to focus on what matters most.
Amid all this change, Lorikeet AI has popped up as a name worth knowing. It’s built for businesses that really can’t afford slip-ups, particularly those in regulated spaces like fintech and healthtech. Their big promise is automating tricky, multi-step support tasks with the same precision as your top human agent. But is it the right tool for every single team?
In this honest Lorikeet AI review, we’ll walk you through its core features, the tech behind it, its pricing, and where it might have some drawbacks. We’ll look at what it does well and where it might not be the best fit, so you can decide if it makes sense for your support setup.
What is Lorikeet AI?
At its core, Lorikeet AI is an AI support agent designed to handle complicated customer issues from start to finish. It’s not like the old chatbots that just point people to a help article and call it a day. Lorikeet’s main job is to actually solve the problem.
The whole idea behind it is to act like your best human agent. It does this by learning your company’s standard operating procedures (SOPs) and internal workflows, then following them to the letter. This is what lets it handle high-stakes jobs that other AI tools might just escalate to a human, like replacing a lost credit card, processing a refund with multiple steps, or handling sensitive medical questions.
To pull this off, Lorikeet uses its own "Intelligent Graph" architecture. The company says this system is more reliable than some other common AI setups. On one hand, you have basic bots that just pull answers from a knowledge base. On the other, you have more freewheeling "agentic" models that try to figure things out on their own, which can be a bit unpredictable. Lorikeet tries to find a middle ground by breaking big problems into smaller, manageable steps. This approach is all about delivering accuracy and consistency, making it an interesting option for businesses where a wrong answer could cause real trouble.
Key features and capabilities
Alright, let’s get into the nitty-gritty of what Lorikeet AI actually does, from its automation engine to the technology that powers it.
Workflow automation for complex queries
Lorikeet’s biggest strength is automating the kind of tickets that usually end up with your more senior support staff, often called Tier 2 or Tier 3 issues. These are the messy problems that need more than a one-line answer. They often involve checking different systems, following "if-then" logic, and walking through several steps to get to a resolution. Think about a customer asking about a delayed order: the AI might need to check inventory, ping the warehouse, and then update the customer. Or imagine handling a multi-step "Know Your Customer" (KYC) review for a finance app.
This is a huge deal for businesses that run on clear, documented procedures. If you have a playbook that spells out exactly how your team solves problems, Lorikeet is designed to take that playbook and run with it, 24/7.
But while this structured approach is solid, setting up these workflows can take a lot of engineering time and back-and-forth with the vendor. For teams that need to be a bit more nimble, a tool like eesel AI gives you a simple prompt editor to build your own custom workflows. This means your support team can define, test, and tweak automation rules themselves, without getting stuck in a long development queue.
The "Intelligent Graph" architecture and reliability
Lorikeet’s "Intelligent Graph" is their solution to one of the biggest anxieties people have with AI: making things up (also known as hallucinations). Instead of letting a large language model (LLM) handle an entire conversation, Lorikeet assigns it small, specific jobs within a set workflow. This greatly reduces the chances of the AI going off-script, which is a must-have in regulated industries. It’s this system that backs up their claims of 99% accuracy and big jumps in customer satisfaction scores.
This is one way to build trust in an AI tool. Another, more hands-on way is to see how it performs with your own data before you flip the switch. For example, eesel AI lets you run risk-free simulations on thousands of your actual past support tickets. This gives you a clear, data-driven picture of what your resolution rates, accuracy, and cost savings will look like before a single customer ever interacts with it. It’s about proving the value upfront, not just taking the architecture at its word.
Integrations and channels
Lorikeet connects with major help desks like Zendesk and Intercom, along with business tools like Stripe and Shopify. This allows it to fetch information and perform actions in the systems your team already lives in. It’s also built to work across different channels, whether it’s chat, email, or even voice.
Connecting to your help desk is a basic requirement these days, but real automation needs more than that. It needs to tap into all of your company’s knowledge, no matter where it’s stored. eesel AI offers over 100 one-click integrations, so it connects not just to your help desk but also to all the scattered knowledge sources your team uses. This could be internal guides in Confluence, project specs in Notion, or shared documents in Google Docs. By learning from past tickets, help articles, and your internal docs, the AI gets a complete picture of how to solve problems just like your team does.
Potential limitations
No tool is a perfect fit for everyone. Lorikeet’s specialized, hands-on approach comes with some trade-offs you should think about, especially if your team needs to move fast and stay in control.
The setup process (power vs. speed)
Lorikeet is built to handle really specific, complex problems. That level of customization usually means a longer, more involved setup process. For enterprise AI tools like this, it’s not unusual for a full deployment to take anywhere from 6 to 12 months, often requiring a lot of help from the vendor’s team or your own engineers.
That timeline can be a dealbreaker for teams that need to see results sooner rather than later. In contrast, a platform like eesel AI’s is completely self-serve. You can connect your help desk, train the AI on your data, and have it running in minutes, not months. That’s a huge plus for teams that want to start automating tickets and improving efficiency this week, not next year.
An all-or-nothing approach to automation
If you look at Lorikeet’s materials, you’ll see they aren’t big fans of AI copilots, calling them a "band-aid." This points to a rigid, automation-first philosophy that might not work for every team. A lot of support teams prefer to ease into AI, starting with tools that assist their human agents. This helps speed up workflows and builds trust before they’re ready to let an AI agent work completely on its own.
An all-or-nothing approach asks you to take a pretty big leap. That’s why eesel AI offers a bit of everything. You get a powerful AI Agent for full automation, but you also get an AI Copilot that works alongside your team, drafting replies and suggesting next steps. This lets your team choose its own automation journey, starting wherever you’re comfortable and scaling up when you’re ready.
Pricing and transparency
Lorikeet’s pricing starts at $500 a month, but after that, the details get a bit fuzzy. It’s not clear from their website how the price changes as you grow, what features are in different plans, or if there are extra fees for setup and support. This lack of clarity can make it tough to budget accurately and know what you’re really signing up for.
Business tools shouldn’t come with financial surprises. eesel AI’s pricing is upfront and easy to understand. The plans are based on feature tiers and a set number of AI interactions, so you won’t get a surprise bill with per-resolution fees after a busy month. We offer monthly plans you can cancel anytime, giving you full control over your spending without getting locked into a long contract.
Lorikeet AI vs. eesel AI: A flexible alternative
The choice between Lorikeet and another tool really boils down to your team’s philosophy. Lorikeet is built for deep, highly structured automation that often requires a big upfront investment of time and money. On the other hand, eesel AI is designed for speed, flexibility, and control, putting the power to build, test, and launch AI assistance right in the hands of the support team.
Here’s a quick table to break down the key differences:
| Feature | Lorikeet AI | eesel AI |
|---|---|---|
| Onboarding Speed | Likely weeks or months; requires vendor help | Go live in minutes; completely self-serve |
| Automation Flexibility | Agent-only approach; no copilot option | All-in-one: AI Agent, AI Copilot, and AI Triage |
| Workflow Customization | Great for rigid SOPs, but likely vendor-configured | Fully customizable with a simple prompt editor |
| Testing & Simulation | Offers simulation tools | Simulate on thousands of your past tickets before launch |
| Knowledge Sources | Focuses on helpdesk and SOPs | 100+ integrations (Google Docs, Confluence, etc.) |
| Pricing Model | Starts at $500/mo; scaling details are unclear | Transparent tiers, no per-resolution fees, monthly plans |
Choosing the right AI partner
So, what’s the bottom line in this Lorikeet AI review? It’s clearly a powerful, specialized tool. For a large company with complex, unchanging workflows and the budget for a long, vendor-led implementation, it could be a great choice. Its laser focus on reliability in high-stakes situations is its main appeal.
In this video, Lorikeet's co-founder Steve Hind discusses what makes their approach to AI support different and how they are building more reliable AI agents.
However, for most teams out there who need to move quickly and want to stay in the driver’s seat, a different kind of solution probably makes more sense. The best AI partner is one that bends to your workflows, not the other way around. It should feel like a natural part of your team, helping you automate things on your own terms.
The real question you should be asking is: do you need an AI solution you can get up and running this week, or are you prepared to wait until next quarter?
Get started with a smarter, faster AI agent
If you’re looking for an AI support platform you can set up yourself in minutes, one that gives you total control over automation and instantly connects to all the places your team knowledge lives, then eesel AI was built for you. You don’t have to sit through long sales calls or wait on custom engineering projects to start seeing a difference.
or book a no-pressure demo to see how you can bring smart automation to your support team today.
Frequently asked questions
Lorikeet AI is an advanced AI support agent designed to fully automate complex, multi-step customer issues. It aims to solve high-stakes problems by learning and executing your company’s standard operating procedures with precision.
Lorikeet AI is best suited for businesses, especially those in regulated industries like fintech and healthtech, that handle intricate support tickets requiring high accuracy and adherence to strict protocols. It excels where precise, documented workflows are paramount.
A full deployment of Lorikeet AI typically involves a significant setup process, often ranging from 6 to 12 months. This extended timeline usually requires substantial collaboration with the vendor’s team or dedicated internal engineering resources.
Yes, this review suggests Lorikeet AI tends towards an automation-first, all-or-nothing approach, often viewing AI copilots as insufficient. This means it’s geared for full agent replacement rather than flexible human-AI collaboration.
The pricing details for Lorikeet AI are noted as somewhat opaque after the initial $500/month starting point. The blog indicates a lack of clear information regarding scaling costs, feature tiers, or potential extra fees.
The "Intelligent Graph" architecture enhances reliability by breaking complex problems into smaller, manageable steps, assigning specific tasks to the LLM. This structured approach significantly reduces the risk of AI hallucinations and ensures consistent, accurate responses.
