Common situation

You tried AI, but nothing changed

Someone tested ChatGPT or Copilot, a few people use it now and then, and the work looks the same as before.

What it looks like
- Licences were bought, but only a few people open the tool, and only now and then.
- Each person uses AI in their own way, so the result depends on who did the work.
- A pilot looked promising, then nobody had time to connect it to the real systems.
- Nobody can say how many hours AI saves today, or whether it saves any.
What it costs you

Licences keep costing money every month while the work stays the same. Worse, the team decides that AI does not work for a business like yours, and the next good idea is harder to start.
How we fix it

We start from one process that matters, such as a shared inbox, supplier invoices or a weekly report, and measure how long it takes today. Then we build AI into the steps people already follow, inside the systems they already use, instead of asking them to open another tool.
After a few weeks we measure again, train the team and adjust what does not work. You see the difference in hours and errors, not in impressions.

What the solution can look like

These are examples. Every solution is sized to the problem, and sometimes a better process is all it takes.

Rhyline Inbox

Every email to a shared inbox is read, sorted by topic and urgency, and passed to the right person with a summary and a draft reply that someone approves.
Rhyline Reader

AI reads invoices, orders or forms, from a PDF or a phone photo, and fills in the data for a person to check and approve.
Rhyline Data

Managers ask questions about sales, hours, invoices, stock or production in plain language and get the figure, a chart and the calculation behind it.