Let's look behind the numbers.
Most monitoring watches a few totals, which hide where a change starts, and most models are retrained overnight or weekly by reprocessing their history. Gemsen gives each station, product, stock or account its own learning engine. Each engine takes in the newest data and drops the oldest without going back over the history, so thousands of them stay current at once.
You ask in plain English. A language model works out what you are asking and writes the answer, but code computes every figure, and each figure is checked against the data before you see it. When the data cannot answer a question, the answer says so.
When the data can’t answer. No ticket prices at the agency, no commission data at the desk. Each answer said so.
Each alert asks your team whether it agrees. A verdict makes that learning engine a little more sensitive or a little less, and every change sits in a log with its reason, so anyone can see why the system behaves as it does. Over time the log becomes your team’s judgment, kept and put to work.
We give you the tools. You bring the insight. Together, we improve accuracy.
If you choose, it can run entirely inside your own environment, and the data stays secure.
A transit agency, an online store and a trading desk run together on one dashboard, with the learning engines, the AI and the checks included. A new data flow plugs into the same system. Gemsen sets it up, so your team does not need data scientists of its own.
The figures for the agency, the store and the desk come from recorded runs of the Gemsen dashboard. Results marked as a planted test come from changes we hid in real data to check that the system finds them.