Startup secured $9M funding on February 2nd, 2024
Let’s be honest — we’re all tired of those annoying first-generation AI chatbots that started popping up everywhere a couple of years ago. But today, we’re finally entering a new era — one of smarter and more exclusive AI built for customer service. And the startup we’re looking at today is making huge strides in its field — without getting stuck in endless dialogue loops.
Core Idea
Lorikeet has created a customer support AI agent that any other AI support agent should aspire to become.
The startup's AI agent doesn't just answer customer questions — it literally solves the problems that customers face and call support about. Package stuck? Card compromised? Lorikeet's AI agent will handle any such issue (or so the startup claims).
For example, a customer contacts support complaining that they never received the bank card that was supposedly sent to them. Lorikeet can dig into the customer database, find the address where the card was sent, and ask the customer if that’s the correct address.
If the customer says they now have a different address, Lorikeet will update the customer database with the new one. But the process doesn’t stop there!
After all, the customer's initial request was about card delivery. So Lorikeet will also ensure the card is delivered to the new address (or check its delivery status in the database).
And if the card was never actually sent (say, card delivery is only available to premium clients) — it will check whether the card was sent and whether the customer qualifies as a premium client entitled to receive it.
There are four interesting and important points:
The AI is trained for specific tasks using the same instructions that live customer support and service agents are trained with. Lorikeet analyzes all materials and builds its own algorithm for customer interactions, with a wide range of action schemes for various scenarios.
If there’s not enough data to solve the problem, the AI can refer to external materials, including contacting live company employees via corporate messenger.
If there’s still insufficient data or the AI doesn’t have the necessary permissions to perform certain actions, it escalates the issue to an employee who has the needed competencies or rights to help the customer.
And the fourth, no less important point — for every case Lorikeet can't solve on its own, it collects and analyzes the reason and sends it to an admin, so they can upload additional instructions to the platform to handle similar cases in the future.
Standard pricing for the platform ranges from $500/month to $24,000/year, depending on the number of requests the platform needs to handle. Large companies with many requests and a need for complex integrations should contact the startup directly for pricing.
Lorikeet was founded in Australia in 2023. In October last year, it launched its platform and raised its first $5 million in funding. After that, it managed to attract several major clients in healthcare, banking, and crypto. Less than four months after its initial investment round, Lorikeet raised another $9 million in funding.
Fun Facts & Highlights
Customer support is exactly the kind of field where AI is bound to “blow up” the market.
And they are doing it — by forcing us to interact with dumb chatbots that take forever to connect us to a live agent, because the bot itself can’t help us.
That’s exactly what today’s Lorikeet founders are saying, and not without reason: “Few are satisfied with the quality of AI bots that only know how to spit out FAQ answers or act as wrappers that send customer queries to AI engines like OpenAI’s — which are not built to solve this class of problems.”
That’s why Lorikeet's architecture is designed so that its AI agents don’t just exchange messages with users — they solve their problems. And strangely enough, that’s a completely different task. Many chatbots are built to always give the customer an answer — which often leads to endless loops or hallucinations where the bot gives made-up or incorrect information. Unlike them, Lorikeet’s AI agent knows what it doesn’t know — and instantly passes such tasks to human staff.
Also, it’s cool that Lorikeet charges different amounts depending on whether the AI agent simply answers using documentation or needs to build a resolution plan. This lets them use a neat psychological trick.
Because every month, companies will see in their billing statements how many complex cases Lorikeet resolved — reinforcing the sense that this platform is truly essential.
Without it, they’d need to hire live agents to handle that many requests — which would definitely cost more than what they pay Lorikeet to solve the same number of problems.
The startup sticks to very clear positioning of its platform — never claiming that its AI agents are “better” than others. Because words like “better” or “worse” conceptually keep your product in the same category as competitors — leaving customers to choose between them. And often, that choice won’t be in your favor.
Lorikeet makes a bold statement — “our customers use our AI agents to do things no other AI agent can do.” This way, they carve out their own category that only they can occupy.
So the customer is left to choose — either a Lorikeet AI agent, or one of the others that are just better or worse versions of each other.
It’s kind of like Apple. You either use an iPhone, or you use some Android device. And while Apple is a clear identity, with Androids you have to compare, choose, and later explain why your particular Android is better than an iPhone.
Lorikeet doesn’t want to be some Android. They want to be the iPhone in their niche — unique and unmatched.
Where Are We Runnin'?
As we wrote in the article about Operand, after the launch of ChatGPT a few years ago, there was a sudden “explosion” of all kinds of AI assistants — though their core function always boiled down to answering prompts, not solving specific problems. And suddenly, we were surrounded by dumb AI bots that couldn’t actually fix our issues. The same thing happened in almost every sector. And the most ridiculous example, we think, was in sales — a field that’s all about the human factor.
But now that people are coming back to reality, we’re entering a new phase — one where a new generation of AI products is emerging. These can solve far more real-world problems thanks to fundamentally different architectures. Lorikeet is part of this new wave.
The key task now is to seize the moment and carve out a niche for your own product, under the slogan: “Our product does what others can’t.” That’s exactly what Lorikeet is aiming for.
Yes, everyone will eventually copy it. Yes, the functionality will be improved. Yes, it will happen in every market niche. But it’s important to remember that positioning exists precisely to embed itself in people’s minds — to answer the “why” question for them automatically.
In other words, the way you plant this idea in the customer’s mind, how you shift their perception and influence their decisions — that’s what matters.
That’s the essence of positioning theory — you must claim your place in consumers' minds by linking your product to a specific trait. And that link will be expensive and difficult for competitors to override, even if their products learn to do the same thing.
So what’s the answer to the question “Where Are We Runnin’?” today? Create AI agents that solve specialized tasks in niches where they haven’t yet arrived (and trust me — they’ll start appearing everywhere soon). Make it unique, turn your product’s name into a household term, and lock in your positioning. Clear positioning is a huge part of success — as we’ve seen in nearly every project we write about.
What area could you create a next-generation AI assistant in? Where is there still an open niche? And what specific positioning would you choose for it?
About Company
- Name: Lorikeet
- Website: lorikeetcx.ai
- Latest Round: $9M, 02.04.2025
- Total Fundings: $14M, Rounds: 2