You don't scrap a classic because it isn't this year's model. I'm the systems engineer who bridges your existing software and modern AI — using the data you already have, with your own employees checking the AI's work. 35 years in. A small practice by design — senior people, and no layers between you and the builders.
Built for long-term partnership — engagements welcome at any scale.
📘 Author of "The Quantum Hive" — 1,008 pages. A complete blueprint for creating wealth in the AI economy (not UBI). Available on Amazon →
Most AI projects fail — MIT puts it at 95% of $40 billion spent. Not weak technology. Firms sold a fantasy — install AI, fire the staff, let the machine run everything — bolting AI onto businesses they never understood and stripping out the human judgment. The failure wasn't the AI. It was the integration. Integration is exactly what we build, the same disciplined way every time — and why nothing you depend on goes down while we do it. We call those employees Validators — and they're the reason this works.
I start by reading the system you already run. The goal is never to rip it out — it's to find the data and the daily tasks where AI earns its keep. What holds its value stays.
I bridge modern AI onto the data already in your systems, automating the repetitive work that quietly eats your team's hours — without forcing anyone to change how they already do the job.
A Validator is your own employee — the one buried in repetitive work today. AI takes over that grunt work at machine speed; their new job is checking the output and signing off. Same employee, new role: verifying takes minutes, not days, freeing them for higher-value work. Separate verifier models re-check everything first — your people give the final yes. Nothing is trusted until it's verified.
One piece at a time, or several at once — done right, with no disruption, no downtime, and no risk to the applications you already depend on. Savings on the bottom line, not a gamble.
These are examples — not a fixed menu. If a task in your business follows the same logic every time, eats hours, or lives in someone's head, it can probably be built. Here's the kind of thing I mean.
Kills: staff retyping orders from emails, PDFs, and attachments. A system reads the inbound document, pulls the data, and enters it — with the exceptions flagged for a human.
See how it works →Kills: hours spent building quotes by hand. Feed it the spec, the customer, the pricing rules — it returns a priced, formatted proposal ready to send.
See how it works →Kills: stockouts and dead inventory. A system that watches your numbers, forecasts demand, and tells you what to reorder before it's a problem.
See how it works →Kills: staff hunting through catalogs, manuals, and SOPs. An internal assistant trained on your own documents that answers in seconds, in plain language.
See how it works →Kills: hand-keying invoices, purchase orders, forms, and records. A pipeline that extracts what matters, structures it, and flags only what needs a human's eyes.
See how it works →Kills: the fragile spreadsheet your whole operation secretly runs on. A real tool that does the same job without breaking every Monday.
See how it works →Kills: the "our system can't do that" ceiling. I connect modern AI to the older ERP or database you already run — without ripping it out.
See how it works →The industry matters less than the shape of the problem. If your operation moves product, processes paperwork, or coordinates a lot of moving parts — and the real logic lives in old software and a few people's heads — that's exactly where a custom build pays for itself. A few examples, not a limit:
Order entry, customer-specific pricing, PO matching, inventory, returns — the daily grind that legacy ERP never quite handles.
Freight and customs paperwork, status updates, document handoffs, and the coordination tasks that eat a coordinator's whole day.
Quoting, scheduling, job tracking, and the back-and-forth that keeps an owner at the desk instead of running the business.
Correspondence processing, document extraction, and the repetitive back-office data work built to your own standards.
Intake, records handling, and follow-up automation for the front desk and admin side — the paperwork no one has time for.
Quoting, job tracking, and the spreadsheet-and-tribal-knowledge systems that don't scale past a certain size.
The hard part of AI was never the model. It's understanding the operation it has to fit into. That's the part I've been doing my entire career.
Decades across federal procurement systems, RPG programming, and process engineering — order-to-cash, inventory, purchasing, the real logic underneath the software. I've built systems for environments where getting it wrong wasn't an option.
Plenty of distributors and operators still run on older ERP and databases that "can't do AI." I can read those systems and bridge modern AI to them — without forcing you to rip out what already works.
I don't resell one product with your logo on it. I design the system around how your business works — which means it fits the way your people already do the job, instead of forcing them to change.
A small practice by design — senior people working in concert, matched to the size and complexity of your project. No account managers, no handoffs to a stranger — from first call to delivery, you deal with the people responsible for the outcome.
Custom work starts with understanding the problem, not quoting a number. Here's the path from first conversation to a system your team owns.
A real discussion of how your business runs and where the time and errors go. No charge, no sales pitch — just figuring out if there's something worth building.
A clear scope and a fixed quote, tailored to your project. Timeline is set together, based on the actual work — never a number pulled from thin air.
The system is designed around how your people already work. I architect and oversee every build, bringing in specialized resources as the scope requires.
We run it against real cases, find the edges, and tighten it until it holds up in your day-to-day — not just in a demo.
Your team is trained to own it. I'm there for updates and expansion when you need it — without locking you into anything.
Every one of these is built into how I work — not written on a wall.
You see the full scope and a fixed quote in writing before work begins. No surprise invoices, no scope creep billing — you approve, then I start.
No account managers. No handoffs to a stranger. From first call to final delivery, you work with the senior people who design the system and stand behind it.
Every deliverable is built for the person who has to use it. No jargon, no filler. If your team can't run it without me, I haven't finished the job.
If your project isn't something I should take on, I tell you on the first call — before you spend anything. I'd rather pass than waste your time.
Your files, data, and business information are never shared. Handled to the standard of any professional office. NDAs available on request.
I train your team to run it and don't leave you dependent on me. Quality and fit come first — built to last, not rushed out the door.
A straight conversation about what your business needs — what's worth building, and what it would take. No account managers. No obligation.
These are illustrative examples of the kind of work I take on, not a fixed catalog. The real answer to "can you build X?" almost always starts with a conversation about how your business actually runs. If a task is repetitive, error-prone, or trapped in one person's head, it's a candidate.
Your people retype the same information off inbound emails, PDFs, and attachments all day — and a typo becomes a wrong shipment. We build a system that reads the inbound document, pulls out the order or intake data, drops it where it belongs, and flags only the exceptions that actually need a human. The routine 90% handles itself; your staff spend their time on the 10% that matters.
Building a quote by hand means digging through pricing, applying the right customer tier, checking availability, and formatting it so it looks professional — every single time. We build a tool that takes the inputs, applies your pricing rules and customer-specific terms, and returns a clean, priced proposal ready to send. The judgment stays yours; the busywork disappears.
Your staff lose time hunting through catalogs, price lists, manuals, and SOPs — or interrupting the one person who knows the answer. We build an internal assistant trained on your own documents that answers questions in plain language, in seconds, with the source it pulled from. It's institutional knowledge that doesn't walk out the door when someone retires.
Document-heavy businesses generate more paper than staff can key in by hand — invoices, purchase orders, packing slips, applications, records, and correspondence. We build pipelines that read those documents, pull out the fields that matter, structure the data, drop it where it belongs, and flag only the exceptions a person needs to look at. The routine volume handles itself; your team stops being a human data-entry line.
This is the catch-all for everything that doesn't fit a neat box — and where decades of systems experience matters most. A lot of real businesses run on older ERP, databases, and systems that "can't do AI," held together by spreadsheets that quietly run the whole operation. I read those systems, bridge modern AI and automation to them, replace the fragile spreadsheet with a real tool, and connect the things that don't talk to each other. If you can describe the problem, it can usually be built — whatever your industry.
These are examples, not limits. The real work starts with a conversation about how your business runs — then we figure out what's worth building.
Every business runs differently, so every project is scoped to the actual work in front of it. Here's exactly what happens from the first call to a finished system your team owns — and honest answers to the questions everyone asks.
Fair question — and the honest answer is that it depends on the work. A focused tool that solves one problem is a very different project from a system that ties into your existing software. Rather than post a number that won't fit your situation, I scope each project individually and put a fixed quote in front of you before any work starts. No surprise invoices, no scope-creep billing. The first conversation is where we figure out whether a project is worth doing at all — and that costs you nothing.
A few things hold true on every engagement, regardless of what's being built:
Tell me how your business runs and where it hurts. If there's something worth building, I'll scope it and put a fixed quote in front of you. If there isn't, I'll tell you that too. Call (561) 316-6794 or use the contact form.
I'm Michael Macchiarella. Before Luxvaro, I spent 35 years in the unglamorous part of technology that actually runs businesses: federal procurement systems, RPG programming, and process engineering across government and private-sector operations. The thread through all of it is the same — understanding how an organization really works, then building systems that make it manageable, auditable, and sustainable.
That background matters more now than ever. RPG and legacy ERP were the backbone of wholesale, distribution, and operations software for decades — order-to-cash, inventory, purchasing, the logic underneath the screens. A lot of real businesses still run on those systems and can't find anyone who understands both the old machinery and modern AI. I do. I can read what you're running and bridge new capability onto it without forcing you to tear it out.
Most of the AI services world right now is people who discovered these tools last year, selling the same chatbot to everyone. AI tools are genuinely powerful — but the hard part was never the model. It's understanding the operation the system has to fit into, where the edge cases hide, and how to build something a team will actually use a year from now. That judgment comes from doing the work for decades, not reading about it for months.
I think about this seriously enough that I wrote a book on it — The Quantum Hive (2026), on AI and the future of work. The core argument is the same one behind how I build: AI is powerful but blind, and human judgment is what turns raw AI output into something a business can actually trust. That conviction is exactly what I bring to every system I design — it's the principle behind what I call the Validator Method: keep what works, add the intelligence, and keep your people in charge as the validators.
I built Luxvaro to do one thing well: design and build the custom system a business actually needs, working directly with the owner — not through account managers or handoffs. I architect and stand behind every engagement, and bring in specialized resources as a project's scope requires, the same way any systems shop operates.
You see the full scope and a fixed quote in writing before work begins. No surprise invoices, no scope-creep billing.
Every deliverable is built for the person who has to use it. If your team can't run it without me, I haven't finished.
Your information is never shared. Handled to the standard of any professional office. NDAs available on request.
If your project isn't something I should take on, I tell you on the first call — before you spend anything at all.
No account managers. No handoffs. Direct access from first conversation to final delivery.
The fastest way to know if I can help is a short conversation. Tell me how your business runs and where it hurts, and I'll tell you honestly whether there's something worth building — no charge, no obligation, no sales pitch.