The same fan, recognized everywhere — even when the data disagrees.
Matching records by rules alone leaves money on the table: the same fan, spelled two ways across two systems, often scores just below the bar to merge automatically. athvin pairs a statistical matching engine with the Replay Booth — an AI adjudicator that reviews exactly those borderline cases, merging the ones it can confidently confirm and flagging the rest for a human. Here is how it works.
First, the math decides what it can.
Every candidate pair gets a match-confidence score. High scores merge automatically and the lowest are dropped. In between sits the gray zone — pairs too risky to auto-merge, yet too similar to ignore.
Then the AI does the extra leg.
Each gray-zone pair goes to the Replay Booth, which weighs the records and the model's own evidence and returns a verdict with a confidence score — auto-merging the clear matches, routing the genuinely ambiguous ones to a human, and rejecting the rest.
How a borderline pair gets judged.
The model shows the Replay Booth the two records and a field-by-field breakdown of what supports or argues against a match. Watch a confident merge and a careful rejection.
“Rob” is a common short form of “Robert.” An identical date of birth and an identical phone number are powerful corroboration; different email providers usually mean two accounts for one person, not two people.
✓ Same person — merge · 94% confidentMore records unified — every call on the record.
Statistical matching does the heavy lifting; the AI recovers the merges it would otherwise leave on the table. Figures below are illustrative of a single resolution run.
Nothing merges silently. Every AI decision is written to an immutable audit trail — the two records, the model's evidence, the verdict, the confidence, and whether it was applied — so your team can review any call at any time.
| Pair | Decision | Confidence | Status |
|---|---|---|---|
| ATH-2847 ↔ TKT-5519 | Merge | 94% | applied |
| ATH-1180 ↔ CRM-3304 | No match | 96% | logged |
| ATH-0942 ↔ DON-7781 | Review | 78% | queued for human |
Too close to call? It goes to the Replay Booth.
When two records land in the gray zone — too alike to keep apart, not alike enough to merge on the rules alone — athvin sends the pair to the Replay Booth. Like an official reviewing a contested call, it weighs the evidence, confirms the calls it can stand behind, and sends the genuine toss-ups to your team. Every ruling is recorded.
Reviews the close calls
The statistical engine auto-merges the confident pairs. The Replay Booth only steps in for the borderline matches that score too close to call.
Makes the ruling
It weighs the evidence across name, contact details, and behavior — confirming the merges it can stand behind and sending the real toss-ups to a human.
Shows the tape
Every decision comes with a written rationale and a full audit trail, so you can always see exactly why a call was made.
Find the fans you didn't know you already had.
We'll connect a sample of your systems and show you the duplicate fans athvin resolves — including the borderline merges your current tools miss.