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.

Personalised AI Workflows for Legal & Accounting Firms

In the world of law and accounting, information is both the life-blood and the bane of an organisation. **Most firms wrestle with scattered data, disparate processes, and the perennial problem of too many tools with not enough integration.** As I discussed recently with a partner at a leading law firm, the crux of the issue is the same: there's rarely a single source of truth that aligns with firm-specific processes. This is where personalised specialist AI workflows step into the limelight.

The myth of one-size-fits-all

The allure of one-size-fits-all solutions is strong — plug it in, and you’re done. However, anyone in a law or accounting firm knows this is largely a myth. The processes that work for corporate law do not fit family law, just as tax accounting diverges greatly from audit work. Attempting to shove these distinct disciplines into a uniform system often results in inefficiencies that undermine productivity and accuracy.

Why a single source of truth matters

Enter the concept of a single source of truth — a cohesive hub where all data resides, verified and trusted. This approach provides a bedrock for complex decisions, ensuring that everyone is on the same page. Yet, the beauty lies not just in having a single source but in how cleverly it can integrate with AI solutions tailored to specific needs.

Our journey at hmn.plus with Agentic OS has shown the importance of aligning technology with specialised processes. We built this to enable personalisation within AI workflows, ensuring that each specialist within a firm can tap into their zone of genius without the friction of clunky, generic systems.

Personalisation: More than just a buzzword

In the conversation with the law firm partner, the key takeaway was that personalisation isn't just a nice-to-have — it's a necessity. Law firms, much like their accounting counterparts, operate under unique methods that reflect their expertise, client bases, and regulatory requirements. Broad-brush AI solutions often miss the subtle nuances required.

With Agentic OS, we’ve made it possible for AI workflows to respect internal processes. For example, a litigation team might need an entirely different flow compared to their colleagues in mergers and acquisitions. Our dynamic system adapts its AI-driven capabilities, understanding the specific language, data formats, and steps each practice area requires.

Outcome over activity

**When AI workflows align perfectly with individual practice areas and serve as an extension of their core functions, the focus shifts from activity to outcomes.** Rather than being bogged down by managing disparate tools and processes, firms can concentrate on delivering results. This is more human per hour — allowing talent to shine by reducing manual, low-value tasks.

Strategic before tactical integration

Strategically integrating personalised AI workflows isn’t just about connecting systems. It’s about enhancing them to reflect the way human experts naturally think and work. Our integration effort prioritizes strategic alignment — understanding the bespoke requirements of each sector before implementing tactical solutions.

Ultimately, the goal is to craft a system that not only meets immediate needs but grows as a firm does. The journey with personalised AI workflows begins with understanding that true innovation requires humility — recognising it’s about more than just technology. It’s about crafting an environment that mirrors the rigour and precision demanded by specialised practice.