We didn't start FluxCo because we thought the world needed another AI consultancy. We started it because we kept watching the same thing happen.
A business has a real problem. They talk to an AI company. They get a slide deck, a strategy roadmap, maybe a proof of concept that lives on someone's laptop. Six months later, nothing has changed. The problem is still there. The budget is gone.
We've sat on both sides of that table. Between us, our team has spent years building software across Big 4 consulting, banking, ERP implementations, hospitality tech, enterprise software, and property management. We've seen how organizations buy AI. Most of the money goes to planning. Very little goes to building.
FluxCo exists because we think that's backwards.
Build First, Deck Later
Our first project was for a property management company. Their team was walking through buildings, taking notes on their phones, then spending hours formatting and transferring those notes into Confluence pages. We built a Slack bot that takes voice notes, parses them into structured templates, and saves them to Confluence automatically. Property managers talk into their phone on-site, and structured documentation appears without anyone typing a word.
We didn't pitch it with a deck. We built it, put it in their hands, and iterated from there.
Then came Arch Convert. Two architects, one from New Zealand and one from the UK, both working in Vancouver. They were converting measurements between imperial and metric dozens of times a day. Canada designs in metric but builds with American materials measured in imperial. Every spec sheet is a conversion exercise.
We sat down with them and built the first version of Arch Convert that night, live prototyping with real feedback. Two weeks of iteration later, it was in daily use across their firm.
That's not how consulting usually works. But it's how useful software gets made.
The Pattern We Keep Seeing
Every project we've taken on has followed the same shape. Someone has a problem that sounds specific and unglamorous. It's not "revolutionize our industry with AI." It's "I spend three hours a day on this thing and it's killing me."
A property manager was drowning in tenant dispute calculations. Multiple claims, overlapping deductions, aggregate exposure across a portfolio. They were doing it all in spreadsheets. We built a calculator that models each dispute and aggregates them into a single financial picture. What used to take a day of spreadsheet wrangling now takes ten minutes.
None of these are flashy AI demos. They're all in production, being used by real people, solving problems that existed before we showed up.
The Difficulty of Building Is Disappearing
We've spent our careers building software. And we've never seen anything like what's happening right now.
The cost of building a solution has collapsed. Things that used to take a team of five and three months can now be prototyped in a day and shipped in a week. That's not hype. We're doing it.
Five years ago, building a voice-to-documentation pipeline for a single property management company wouldn't have made financial sense. The development cost would have been too high for the return. Now we can prototype it in a day and ship it in a week. The economics flip completely.
This is the most disruptive time in software. The barrier to building useful things is falling so fast that the bottleneck is no longer technical capability. It's knowing which problem to solve and getting the solution into someone's hands fast enough to learn from it.
That's the opportunity we keep finding. Problems that were always solvable but never worth solving at the old cost structure. AI doesn't make these problems new. It makes the solutions feasible.
What We've Learned
After a year of building this way, a few things have become clear.
Speed matters more than polish. A working prototype in someone's hands tomorrow is worth more than a perfect product six months from now. Every project we've shipped started rough and got better through real usage. The architects using Arch Convert shaped it into something we never would have designed in isolation.
The right clients understand their own problem. We work best with people who know what's broken in their workflow and are willing to try something new. Size doesn't matter. What matters is that you understand the problem, you're open to prototyping fast, and you want to get a tool into real users' hands for feedback as quickly as possible. That's the type of engagement where AI delivers real outcomes.
Cross-industry experience is an advantage. We've worked in enough different fields to see patterns. Problems repeat across industries. If you've seen enough of them, you recognize the shape faster.
AI is a tool, not a strategy. The businesses that benefit most from AI are the ones that start with a clear problem, not a desire to "do AI." We turn down projects where the goal is to use AI for its own sake. If the problem doesn't justify the tool, we'll say so.
What's Next
We're based in Vancouver and Auckland. We work with businesses across industries, and we're always looking for the next problem that's been waiting for a better solution.
If you have something specific in mind, reach out to discuss. If you're not sure whether AI fits your problem, that's fine too. We'll tell you honestly.
FAQ
How is FluxCo different from other AI consultancies?
We build and ship. Most consultancies sell strategy and leave implementation to you. We do both, and we bias toward building first. If we can prototype something in a day, we'd rather show you a working tool than a slide deck.
What industries do you work in?
We don't limit by industry. We've worked with architecture firms, property managers, real estate platforms, and service companies. The common thread is a real, specific problem where AI or automation makes the solution feasible.
How quickly can you build something?
It depends on scope, but our fastest projects have gone from conversation to working prototype overnight. Most projects take one to three weeks from kickoff to production. We'll give you a realistic timeline after understanding your problem.
If you found this useful and have a problem you'd like us to solve, reach out to discuss.