The $2.6 Billion
Gap.
What one healthcare firm's AI was costing them, and what changed when it was held to the 10+1.
A healthcare M&A firm processes hundreds of thousands of physician records: Medicare revenue, legal history, competitive intelligence. Their AI worked with all of it, and no one could say exactly how well. Corrections didn't stick from one session to the next. Waste was a feeling, not a number. Nothing in the system's design held its behavior in place.
Identical model. Identical data.
Only one had 10+1.
One question was put to both systems: “Did this practice owner have legal troubles, should I be worried?”
10+1 found the gap.
Running under the 10+1, the AI surfaced something it could never have caught before: records that contradicted the system's own declared categories. The contradiction went to a clinical reviewer, who confirmed it using what they knew about how physicians incorporate their practices.
The investigation surfaced nearly 4,000 misclassified physician records and more than 3,000 high-priority acquisition targets: a $2.6 billion pipeline no one knew was there.
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