What is your decision based on?

Application screening, request classification, priority order and risk flags are decided by the same rule every day. Today that rule lives in a policy document or in people's heads. The system puts it in writing, passes every record through the same measure, and writes the reasoning next to it; a person still makes the call.

Book a discovery call See how the score is built

Systems we connect to

HubSpot
PostgreSQL
Supabase
Airtable
n8n
Claude
Your own panels

More than visibility

Making a decision is easy.Making the same one forty times is hard.

Of two similar records one passes and the other sits on the line. Where the difference came from is visible in the system: which rule, which field, which threshold. Because the measure is written, the outcome does not shift with who is looking or what time it is.

Every record passes the same measure

The rule you wrote is applied to every record the same way. When the rule changes, new records are assessed with the new version and decisions already made stay as they are.

Records on the line are flagged

A record inside the rule passes automatically; one sitting on the line is flagged and goes to the decision owner. You draw that line, and the system does not widen it on its own.

Decision history accumulates

Decisions and their reasoning are written to the audit log. A month later, why the same question got a different answer is read off one screen.

Why it matters

A decision that repeatsis attention wearing out.

If a measure is written down, applying it is repetitive work, and repetitive work produces errors by the end of the day. When the system does the first pass, a person only looks at the record on the line and their attention collects there. Every suggestion comes out with the rule behind it; no decision is asked for without the reasoning in view.

How the score is built

One outcome.A written rule behind it.

Every assessment comes from the measures you wrote; the system cannot invent a new one on its own. Because the measure, the threshold and the exceptions are put in writing during discovery, where an outcome came from is always visible.

Rule version per record

Every decision carries the version of the measure it was made under. When two people look at the same record the outcome matches, and the difference stops being a topic of argument.

Suggestions without reasoning

No suggestion is produced without writing down which rule, which field and which value decided the outcome. If the reasoning is empty, the record goes to a person.

4-8

Weeks to the first live workflow

Varies with the number of rules, data quality and where the automatic-pass line sits; the exact timeline is written into the discovery report.

Rule

The measure, the threshold and the exceptions in written form. You write them, we turn them into a system; no rule goes live without your approval.

Line

Which decision passes automatically and which goes to a person. Drawn together during the build and changeable whenever you want.

Reasoning

Next to every suggestion, which rule, which field and which value decided the outcome is written down.

Audit log

Which decision was made when, by whom, and under which rule version. It helps in an audit, but its real purpose is that the team can trust the outcome.

Deviation

The share of decisions falling outside the rule. Watched monthly; a rising deviation means the rule needs refining.

Frequently asked

Repeatable decision supportFrequently asked questions

No. The system applies the rule, classifies the record and writes the reasoning. If you want automatic passing for records that sit inside the rule, you draw that line; even then, which rule it passed under stays on the record.

You write them and we turn them into a system. The measures that live today in a policy document or in people's heads are put in writing during discovery; no rule goes live without your approval.

It is not left free. The assessment is bound to the fields and thresholds you wrote; the model cannot invent a measure outside them. A record it is unsure about is not classified; it is flagged and left to a person.

The rule is written openly, every suggestion goes into the audit log with its reasoning, and the share of decisions outside the rule is watched monthly. Bias becomes visible inside the written rule rather than inside a model, and that is where it gets corrected.

The data stays on your own infrastructure and is not used to train models. Which fields enter the assessment is written during the build; a field that is not on the list never reaches the system.

They stay as they are. Every decision carries the rule version it was made under; retroactive reassessment runs only if you ask for it.

Discovery takes a week. In that week we put in writing who decides what, and on what basis, today. The first live workflow opens within 4-8 weeks; the range depends on the number of rules, data quality and where the automatic-pass line sits. Your own timeline is written into the discovery report.

Two numbers are measured at the start: the average time to assess a record, and how often different people reach different decisions on the same record. Both are measured again after the workflow opens, and are watched monthly in the report alongside the share of decisions falling outside the rule.