Zyplux
We connect a private AI agent to the systems your business already runs on — email, spreadsheets, databases — and give it the repetitive, multi-step work that fills your team’s week. It works around the clock, nothing goes out without your approval — and when the work reaches your customers, we build that too.
No call required. Real findings in days.
We start with your system, not our software.
Every business is a set of loops. An order comes in, it’s filled, invoiced, paid — and the cash funds the next order. A customer asks, gets an answer, comes back. When a loop runs clean, the business grows. When it snags — a step done by hand, a hand-off that drops things, a report nobody has time to read — the whole system slows, and you feel it as lost hours and missed money.
So before we build anything, we learn your loops. We sit with how the work actually happens — not the org chart, the real flow — and find the few places where a small change pays back the most. Then we put intelligence exactly there.
That’s the order we work in: understand the system, fall for the problem, then walk back to the technology. The software is the last decision, not the first.
Map the loops.
We trace how work, money, and information move through your business — and where they stall.
Find the pressure points.
The handful of spots where one change returns the most hours, the most cash, at the least risk.
Put intelligence there.
An agent, a dashboard, or an app your customers touch — whatever the spot actually needs. Built around your loop, not bolted on.
What a week with Zyplux looks like.
Monday, 2:14 AM — a supplier emails an invoice.
Zyplux reads it, finds the matching purchase order in your system, spots that the total is $312 over, and queues it for your bookkeeper with the discrepancy highlighted. They’ll see it at 9:00 — already checked.
Filed, matched, flagged — before anyone was awake.
Monday, 7:30 AM — the weekly report wrote itself.
Sales, deliveries, complaints, cash — pulled from your own systems, summarized in plain language, in your inbox before your first coffee. The same report that used to take someone their whole Monday morning.
Done. Every Monday. Without fail.
Tuesday, 9:05 AM — "Where is my order?"
A customer emails. Zyplux finds their order in your database and drafts a reply with the delivery date and tracking link. Your support person reads it and clicks Approve. Sixty seconds — not an afternoon of digging.
Answered fast. Approved by a human.
Friday, 8 AM — a question worth real money.
"Should we take on the second warehouse?" Overnight, Zyplux read your numbers, pulled the market data, and wrote you a two-page brief — with the trade-offs, not just charts.
A decision-ready brief, not a data dump.
These are scenarios — drawn from the workflows we automate. The free audit shows you which ones are hiding in your business.
Three places intelligence pays back.
Once we know your loops, the build is the easy part. It lands in one of three places — sometimes all three.
Close the loop.
The repetitive, multi-step work that fills your team’s week — handled end to end, with a human approving anything that leaves the building. We connect the email, spreadsheets, and tools you already pay for, and tune the loop until it runs on its own — with you watching, not driving.
Hours back. Loops that, over time, run themselves.
Light up the system.
Ask a question in plain language — "how did the north region do last quarter?" — and get a dashboard built from your own data, on the spot.
Answers in seconds, not a ticket to the data team.
Build at the edge.
The software your customers actually touch — a registration page, a booking flow, a mobile app, a website assistant that answers like your best rep. Built fast, because an agent carries the load.
Reach your customers better — and ship in weeks, not quarters.
Ask a question, get a view.
No ticket, no waiting on the data team. Type what you want to know in plain language and a dashboard is assembled from your own data while you watch — a scenario of what "light up the system" looks like.
North region — last quarter
This is not a chatbot
You’ve probably met chatbots. They wait for questions, and they don’t always get the answer right.
An agent is different: it acts. It reads what arrives, checks it against your systems, does the multi-step work, and files the result. You describe the job once — it runs the job every time.
And it knows its limits. Anything that leaves the building — an email to a customer, a payment, a change to your records — waits for a human click. That’s built into the platform, not bolted on.
Acts in your systems
— not in a chat window
Runs jobs end-to-end
— around the clock
Your team approves
— anything that goes out
How this becomes real
Free systems audit.
Tell us how your business runs — or let us take a look. You get back a map of your loops, the three places intelligence pays back fastest — ranked by the hours and cash they’d return — and a plan to build the first one. No call required.
One workflow, live in weeks.
Pick one job from the audit. We connect Zyplux to the systems involved, build the workflow, and run it live. You measure the result before any talk of more.
Run, tune, expand.
We don’t hand over and disappear. We watch the workflow, refine it, and when it has proven its number, we talk about the next one. The pattern is simple: start with one job, grow from the savings.
Who’s behind Zyplux
I’m Sergiy Yeskov, an engineer in Sydney. I’ve spent nearly twenty years building the software businesses run on — thirteen of them on a global logistics platform that companies around the world use for their freight, invoicing, and pricing, where I built the pricing engine and led a team of ten-plus engineers. The last few years I’ve worked purely on AI: systems that read a company’s documents, answer from its own data, and — the hard part — act safely inside it.
I built Zyplux because nothing on the shelf could do that hard part. Plenty of tools can chat about your business; I couldn’t find one I’d trust to work inside it. So I built a platform where approvals, hard limits, and a full log of every action aren’t features bolted on — they’re the foundation it started from.
When you work with Zyplux, you work with me: the engineer who built the platform designs your workflows, connects your systems, and answers your email. No account managers, no hand-offs, no getting passed around.
Your data, your rules
You’d be trusting us with your email, your records, your customers. Here’s how we protect it, plainly:
The agent sees only what you connect.
Access is scoped system by system, permission by permission.
Nothing goes out without approval.
Customer-facing actions wait for a human click — built into the platform itself.
Every action is logged.
A full record of what the agent did, when, and why — yours to inspect at any time.
Your data never trains public AI models.
Your agent runs privately, for your business alone.
Not shared infrastructure spread across thousands of accounts.
Customer-facing work, held to the same standard.
Anything we build for your customers protects their data under the same rules — scoped, logged, never used to train public AI models.
FAQ
How do I know if my business is ready for this?
If anyone on your team retypes information from one system into another, answers the same kind of email every day, or assembles the same report every week — you’re ready. The audit confirms exactly where.
We don’t have clean data or an IT department.
That’s normal, and it’s fine. We work with your systems as they are and carry the technical load. Your team’s only job is to tell us how the work happens today.
How long until we see results?
The audit lands within days. A pilot workflow goes live in weeks, not quarters — and you’ll be counting saved hours from its first week of operation.
Will this replace my employees?
It takes over the most tedious part of their day, not their jobs. The point is to free your best people from retyping data so they can focus on the work you hired them for.
We already have developers — are you just an agency?
Not in the usual sense. We don’t take a spec and bill hours. We find the loop where intelligence pays back, build the smallest thing that proves it, and tune it until it runs. This is usually the work that keeps getting pushed to next quarter.
Can this help us serve our own customers, not just our back office?
Yes. The same method builds the things your customers touch — a registration page, a booking flow, a mobile app, a website assistant. Inside your operations or at the edge with your customers, the approach is identical: find the loop, build for it.
What’s a "dashboard from a question"?
Ask in plain language — "show me last quarter’s refunds by region" — and a view is assembled from your own data while you wait. No ticket, no waiting on the data team. You decide what’s worth keeping.
What happens to our data?
It stays yours. Access is scoped to what you connect, every action is logged, and nothing is ever used to train public AI models. The "Your data, your rules" section above is the short version — we’re glad to walk through the details.
What if the AI makes a mistake?
Occasionally it will — any system can. What matters is what a mistake costs, and here it’s a click, not a customer: outward-facing work is drafted for your approval, every action is logged, and the agent operates inside hard limits we set together.
What happens after you build it?
We stay. Monitoring, tuning, and a direct line to the engineer who built it. Expansion only happens after the first workflow proves its number.
Find out what’s hiding in your week.
The audit is free, takes one short form, and shows you exactly where to start.