Documented automated decisions
Kubli Compass records what every automated decision about a person was based on, at the moment it is made. It produces the documentation the EU AI Act requires for high-risk systems, including differences in behaviour between groups.
Every time the needle settles, the application lands here with its outcome and its reason. There are three exits: approve, decline, and when the signals contradict each other it goes to a person.
The reason column is the only thing that lets you answer someone who asks why they were turned down. It is recorded for the approvals too.
Europe's new rules on artificial intelligence treat automated decisions about people as high risk. In practice that means you will have to show how the system works, not merely that it works.
Sectors
Not just credit
Insurance underwriting
Accepting or declining a policy, with the reason on record and not just the price.
Candidate screening
An automated screening of applications that has to hold up when someone asks why they were ruled out.
Benefit eligibility
A subsidy or public service assigned by a system that has to justify every exclusion.
How it works
Kubli Compass records what every automated decision about a person was based on, at the moment it is made. It produces the documentation the EU AI Act requires for high-risk systems, including differences in behaviour between groups.
Old files hold the complete stories: who saw it through, who stopped, and how long it took. They are also the ones nobody could ever open. Echo makes them usable, Compass trains on them.
The model learns on the treated material and is measured against your real data. If the gap between the two is too wide, Compass flags it and the model does not ship.
If the system behaves differently with different groups of people, the difference is calculated and recorded at every version. It is the first thing an inspection asks for, and almost always the first thing missing.
Versions, data used, results and discarded alternatives are recorded as the work happens. When the time comes to show how the system was built, the material already exists and carries the right dates.
The other modules
Usable archives, measured risk
Kubli Echo produces a usable copy of your archives and measures its re-identification risk with the three attacks the EDPB names: singling out an individual, linking them to another dataset, inferring an attribute. Above the threshold, the file is not released.
Discover EchoAnomalies caught as they happen
Kubli Pulse watches your recurring flows and flags what departs from normal behaviour, before the operation completes. It works on payments, insurance claims, utility usage and returns: the model learns from your own closed cases, not an industry average.
Discover PulseUsable logs, anomalies surfaced
Kubli Sentinel anonymises access and system logs, so you can keep them, share them and analyse them. It then filters the stream and surfaces only what departs from a normal day on your network.
Discover SentinelTwo routes
If you have a problem to solve, start with a demo on your own case. If you are assessing us, as a fund or a procurement team, start with the confidential documentation.
Kubli issues no certifications and holds none. It hands over the measurements taken and the documents to stand behind them when someone asks.
Thirty minutes. You tell us which data is blocked and what you would do with it, and we show you the result on an example close to yours. If the case is not a fit we say so on the call.