Engine A / Automation
You describe the workflow, we make it run itself — and it alerts you when a run fails. Launch is not the finish line: jobs are monitored, crashes trigger notifications, data gets backed up. All of it is inside the deliverable.
▲ Illustrative output, based on the run-log format of an actual scheduling system
Scheduled scraping of web pages, back-office reports, and API data — cleaned, then loaded into a database or spreadsheet. Includes retry-on-failure and data validation. The point is not fetching it once; it is fetching it every single day.
Move notifications, lookups, and reporting into the messenger you already use all day: new-order pushes, low-stock alerts, one command to pull the numbers — no more logging into the back office.
Reports generated on schedule, files backed up on schedule, health checks run on schedule. With run logs and failure alerts: if a job does not run, you are notified right then — not at the end of the month.
Connect systems that do not talk to each other: order data flows into your accounting software, form responses open tickets automatically. Remove the person in the middle whose job is copy-paste.
Fixed-step back-office work — listing products, updating prices, reconciling, exporting reports — written as code. What used to be clicked through row by row now runs itself overnight on a schedule.
Wire AI into the workflow: classify complaints, summarize documents, draft replies. We draw the line between what AI handles and what stays under human review — so AI never speaks to your customers unchecked.
Not slide-deck AI. These two systems were built and run for real iGaming scenarios — capabilities listed below, nothing we can't do.
Intelligent assistant for live-dealer baccarat tables: real-time table recognition and roadmap digitization, a configurable strategy rule engine, automated execution with stop-loss risk control — deployed as a browser extension, no platform modification.
Data and content automation for slot games: game-rule engines, play-data tracking, and automated production of guides and marketing creatives — accurate rules, compelling packaging, ready to feed content sites and communities.
Delivered after platform-terms and local-regulation review. No "guaranteed profit" claims — anyone promising that is usually selling you something else.
Scenario 1 · Daily competitor price checks
Every morning an assistant opens competitor sites one by one and copies prices into Excel. Entries get missed, typos happen, and the moment they take a day off, the data stops.
A crawler fetches at the same time every day and diffs the changes; any price move pushes a Telegram notification. Humans read the results — no manual copying.
Scenario 2 · Multi-platform order reconciliation
At month-end, export reports from the payment backend, e-commerce platforms, and the shipping system, then match rows by hand — a full day spent hunting for the entries that do not line up.
Each platform's data imports into one database daily; the program checks every row and shows humans only the entries that do not match. Human effort goes to handling exceptions, not to confirming what is already correct.
Scenario 3 · Customer status inquiries
A customer asks on LINE, “Where is my case at?” A teammate drops their work to dig through the system, screenshot, and reply — interrupted several times a day.
The bot takes the command, queries the system, and replies with the status; when the status changes, it pushes an update on its own. The interruptions your team no longer gets — that is the actual hours saved.
Describe the task you repeat every day in one sentence — we reply with whether it is feasible and roughly what it costs.
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