Do I need to know what should be automated?

No. Most people arrive with a feeling rather than a specification — something takes too long, or only one person can do it, or it gets dropped whenever the week is busy. That is enough to start from. If you can point at one job you would gladly stop doing by hand, we can work with that. If you can’t point at one yet, start with the free diagnostic instead: it finds the constraint first, and the workflow follows from it.

What happens with the first workflow?

We build it. You describe the job the way you would explain it to somebody starting on Monday — what comes in, what you would check, what should go out, and what you would never let leave without reading it. That becomes a working workflow, connected to the tools you already use, running on your account. You watch it run on real work before you rely on it. One workflow, start to finish, so what you are judging is a thing that works rather than a proposal for one.

What happens after that?

It runs. Keeping it running is the recurring part — hosting, the models it calls, monitoring, and the fixes for when something upstream changes its mind about a field name. Most people then add a second workflow, and it is usually one they spotted themselves while watching the first one work. There is no bundle to commit to up front. The next workflow is a decision you make when you want it, and not before.

Can my team eventually build workflows themselves?

That is the intended end state, and the training exists for it. Once your team has watched a few workflows get built, the skill turns out to be the describing — knowing what the work actually involves and where the judgment sits — which is the part your team already has. Some businesses would rather we kept building, and that is a legitimate choice rather than a failure. Most want at least one person inside who can change something without picking up the phone.

Do I become dependent on hmn.plus?

It is the right question to ask any vendor, and the honest answer is that you can be for exactly as long as it is useful. Three things are deliberate: the workflows are described in plain language rather than locked in a format only we can read, they run on infrastructure that can sit in your own name, and we teach the building instead of keeping it. Being the only people who can change your systems would be a business model. It is not ours.

Can we eventually own the system?

Yes, and it is an option rather than a destination — plenty of businesses would rather we kept running it, and that is a reasonable thing to want. When you do want it, the workflows, their definitions and the infrastructure transfer to you, and your team keeps the training that makes them usable. We would rather you stayed because staying is worth it.

The first automation is a fixed price, so the first decision is a small one: NZ$500 + GST to map it and get it built. After that, the platform it runs on is NZ$150 + GST a month for each person who builds workflows — everyone else who uses it is free — and that covers hosting, running your workflows, monitoring and support. Workflows you build yourself cost nothing extra; the ones we build are quoted one at a time, on what each actually involves. No annual lock-in, and nothing larger to sign before you have seen something of your own working.

Why not use ChatGPT, Claude, Zapier or n8n?

They answer a different question. Chat tools put something capable on the other end of a conversation, and then nothing happens unless a person types — every session starts again, and what the business knows ends up living in whoever writes the best prompt. Zapier and n8n wire apps to each other; the wiring holds until a field name changes, and it never makes a judgment call. Both leave the work depending on a particular person. What we build has a fixed shape: the same steps in the same order, your rules written in, a record of every action and the reason for it, and a person standing where a person should stand. The thinking inside a step can be as sharp as it needs to be. The path through it does not change because somebody phrased something differently. That is the difference between a tool one person is good at and a system a business runs on.

Where should AI actually be used?

On the judgment inside a step, not on the whole step. Reading an enquiry and working out what kind it is: yes. Drafting a reply in your voice, from your own past replies: yes. Moving money, or telling a client something binding, with nobody looking: no. What we build to is that anything with consequences waits for a person, and everything in front of it does not have to. A faster version of a bad process is still a bad process, which is why deciding where AI belongs happens before anything gets built, and is most of the value.

AI in Event Planning: Efficiency with a Human Touch

The challenge of maintaining efficiency and a personal touch

If you've ever managed an event, you know the stress of trying to keep everything organized while still delivering a memorable experience. The sheer amount of manual labor involved in coordinating vendors, juggling schedules, and keeping track of endless details is enough to overwhelm any team. But what if there was a way to lighten that load and free your team to focus on the human side—hospitality, service, and relationship-building?

AI in event planning: A behind-the-scenes powerhouse

At hmn.plus, we've found that artificial intelligence is a game-changer for event management. It's not about replacing humans—it's about enhancing efficiency and freeing your team from the mundane tasks so they can shine where it matters most. Let's break down how AI can help expedite your event planning process.

Streamlining vendor coordination and scheduling

Vendor coordination is traditionally a cumbersome process, involving countless emails, phone calls, and follow-ups. AI can automate much of this. By using smart algorithms, AI systems can match availability, price points, and services more quickly than humanly possible. This allows your team to lock in details faster without sacrificing quality.

Enhancing guest communication

AI-powered chatbots and virtual assistants are now sophisticated enough to handle guest inquiries before, during, and after the event. This ensures that your guests receive timely responses while freeing human staff to handle more complex interactions and personal touches.

Simplifying checklist management and organization

From task lists to timeline tracking, AI can keep your team organized and on top of every detail. Imagine an AI system that not only tracks what's been completed but also anticipates what's needed next—this predictive capability helps prevent last-minute scrambles and keeps the event flowing smoothly.

Making personalization practical

Personalization is key to memorable events. AI can analyze guest data to provide insights that human planners sometimes miss. Whether it's tailoring food and beverage offerings to dietary preferences or customizing event layouts based on past attendee feedback, AI can help you create a more personalized experience without the manual workload.

The human touch: What AI frees your team to focus on

While AI handles the heavy lifting, your team can focus on what machines can't replicate—human interaction. Welcoming guests, providing exceptional service, troubleshooting, and building relationships all require a human touch. By integrating AI into your event planning, you ensure that your team is present and attentive to these crucial elements.

The business case for adopting AI in events

The benefits are clear: faster responses, more organized operations, and a better guest experience. By adopting AI in your event operations, you're not just saving time; you're ensuring that the human elements of hospitality aren't lost in the rush to get things done. It's about crafting an event that feels seamless to your guests, because the real magic of events lies in the harmony between operational excellence and an emotional, human experience.