Till, shifts, cameras, stock and climate across every location. The agent reconciles on its own, collects evidence and writes to you in Telegram only when your decision is needed.
A short call. We pick one loss we can verify and tell you what data is needed.
Chats, cameras, receipts and tasks are sorted into sources, modules and the core. This is the very diagram the agent works by every day.
The agent reconciles, collects evidence and sees it through. You do not need to watch cameras or scroll through ten chats.
If everything is normal — silence. If a decision is needed — the fact, the evidence and the next step.
Food serviceRetailManufacturingGaming arenas
We built this for our own chain first. Below are real screens, data anonymised.
Anywhere with a till, shifts and premises that need to stay under control. Pick your field — below is what the agent takes off your plate first.
You do not open a dashboard in the morning or scroll through cameras. The agent walks the locations itself and writes to you in three cases.
Yesterday's shifts, till against bank, open tasks and overnight events — in one card. Normal does not turn into a stream of notifications.
Fact, time, zone and evidence side by side. The agent says “suspicious event” and “possible discrepancy” — you make the decision from the evidence.
“Done” without confirmation does not close the loop. Unfinished work goes back, finished work goes into the morning summary.
If everything is normal — silence. You get on with your own business.
These are working AGA-agents interfaces from our own chain. Location names, amounts and people are replaced, the structure of the screens is untouched. Click a frame to look closer.
scroll down — the strip moves sidewaysTill, bank, cameras, photo reports and sensors come together in one window. The agent reconciles them itself and brings up only what needs a decision.
To understand how the day went, you open the till, the bank, shift chats and cameras one by one. Time goes into checking, not deciding.
Brings every source into one window and reconciles them against each other. Deviations go to the top, normal days stay quiet.
One window and one Telegram message instead of ten chats. If everything is fine, the agent stays silent.
Sources: till, bank, accounting, cameras, microphones, photo reports, sensors
Cameras and recorders stay as they are. The agent flags a suspicious event with the frame, zone and time, and a person makes the decision.
Cameras record but nobody watches. A guest waits at the desk, litter in a zone, a service given without payment, and you learn about it after the fact or never.
Connects to your existing cameras and recorders, nothing to replace. Flags a suspicious event: guest waiting time, cleanliness and violations by zone, service without payment. Each event is tied to a zone, a time and a shift.
You look at the frame and the reason, not the whole shift. The camera gives an event to check; a person decides.
Sources: Wi-Fi cameras, video recorders
A task waits for evidence and goes back to its owner. A photo gets a verdict against the standard, a recurring problem becomes visible.
“Done” exists only in an employee's message. The manager scrolls through hundreds of photos or does not look at them at all.
The employee shoots the report as before, but it goes to a check against your checklist instead of a chat. A violation becomes a task with the photo for the responsible person. All good, silence.
The manager stops spending hours on review. Unfinished work comes back by itself, violations do not pile up until an inspection.
Sources: employee photo reports from a smartphone
The employee's conversation with the guest becomes a verifiable fact: script followed or not, which phrases sell better for each employee.
A conversation with a guest disappears with the shift. Nobody knows whether the employee greets, offers an upsell or mentions promotions.
Transcribes speech from the till microphone and call recordings and scores every dialogue against markers you set: greeting, upsell, promotions, closing the conversation.
You see who upsells and who does not. The best phrases go into training the rest. We check the effect on the average check on your data. No listening to the whole day by hand.
Sources: microphones at the till and reception, call recordings
Till, bank and POS software live separately, and the difference is found too late. The agent brings the online till, the bank and the books into one place: shortfalls and bookkeeping errors surface as a discrepancy between sources, with evidence and an owner.
Till, bank and accounting live separately. A discrepancy is found a month later, when neither the culprit nor the money can be found.
Continuously brings every money source into one place. A discrepancy between sources becomes an event with evidence and a responsible person.
Shortages and accounting errors show up on the day they happen. You see where to cut costs and where to earn more.
Sources: till, fiscal receipts, POS software, card acquiring, bank, 1C, e-invoicing
Slow-moving goods, a sagging margin, one location's bestsellers missing at another. Purchasing and write-offs from data, not gut feeling.
Stock sits dead for months, margin sags unnoticed, and the bestseller of one location is missing at another.
Pulls purchases, sales and stock from the POS software and documents for every location. Suggests what to order more of, what not to order at all and where a bestseller is sitting on the shelf.
Fewer write-offs and less frozen money, more sales of what people actually buy. Purchasing from data, not habit.
Sources: purchases and sales, stock, POS software
Sensors by zone, lights and air conditioners by schedule and booking, command history for every device.
An empty zone burns light and cooling, air conditioners fight each other because the sensor sits in the remote. Guests are the first to notice a breakdown.
Puts sensors in every zone and knows the bookings. No people and no booking, the zone is not cooled. A guest arrives in half an hour, the zone is ready in advance.
Even climate and happy guests, a smaller electricity bill and less wear on the equipment.
Sources: temperature and air sensors, air conditioners, ventilation, schedule and bookings
Lights, sockets and air conditioners switch on by schedule and booking. Every command is logged, and you see how much each device saved.
Lights and sockets in an empty hall run all night, and nobody knows who switched what on and when.
Connects lights, smart sockets, air conditioners and ventilation. Switches them on and off by schedule and booking and logs every command.
Devices run only when needed. You see the saving for each one, not just the total bill.
Sources: smart sockets, lights, air conditioners, ventilation
From the news hook to publishing on the platforms and returning the links to the content plan. Not a “make a post” button, but a process with proof of publication.
Layout, approval and publishing live in different chats, guest messages in five apps. Nobody knows which post brought in money.
Runs the content plan, prepares images, video and copy, publishes on every platform and returns the links to the plan. Collects guest messages in one window and suggests a reply.
Marketing without manual routine and with proof of publication. Money goes into what works.
Sources: VK, Telegram, MAX, WhatsApp, loyalty system
Each part of the system closes one specific owner's pain. They are connected one at a time, without a big leap.
The agent connects to the online till, the bank and the POS software. Three sources meet in one place: a discrepancy between them is a shortfall, a bookkeeping error or a reason to check an employee, and it is visible at once, not at month end.
The photo gets a verdict, a recurring issue becomes visible, an open action goes back to its owner instead of sinking in a chat. You no longer have to ask “so, what about that”.
With no guests the agent switches off the lights and the air conditioner. Ahead of a booking the climate switches on early, and guests walk into a comfortable room.
The agent sees stale goods, falling margin, and hits in one venue that are missing in another. Purchasing and write-offs come from data, not gut feeling.
You do not need to log into a new app. The agent writes to you when you are needed. A card is what changed, how it is proven and who decides.
Each source takes its own path into its own module. Modules pass facts to the core. The core returns one clear message to you, and a task or a command to the location.
One system, several pains. Parts are connected step by step, in any order.
No. The cabinet is the place for evidence and review. Day to day the agent writes in Telegram, and only when your decision is needed: accept, reject, hand over the task.
No. The camera gives an event to check. The wording is “suspicious event”, “possible discrepancy”, “needs checking”. One frame does not become a verdict. A person decides from the evidence.
No. Existing cameras, till and sources are reused wherever technically possible. We start with what you already have.
For each part of the system the source, permissions, retention period and what may leave the location versus what stays with you are fixed in advance. On this website all real business data has been removed or irreversibly hidden.
Yes, that is the normal path: pick the most expensive verifiable risk, take a baseline, close one loop and only then expand.
The price depends on the number of locations, sources and what we connect. First a short review of the business, then we name the scope and the price.
We do not sell software. We remove one specific headache, show the result and only then expand. No ROI promises out of thin air.
Where your attention goes and where losses are possible. A short conversation, no slide deck.
Only the data and permissions needed for one verifiable risk. Your existing cameras and till stay.
We measure the current state and agree on the criterion for the result.
Signal, action, evidence, re-check. The agent learns from your data and keeps the context.
We will briefly review your location, pick one verifiable risk and show the live screens. No hot air about neural networks.
