The word \u201cnebulous\u201d fits big data perfectly. The patterns are there; the trends rippling;\u00a0 the insights just waiting to be drawn.\u00a0 But they are hazy\u2026unclear\u2026.unformed.\u00a0 Many, many trees.\u00a0 Very big forest.\u00a0 A lot of green.\u00a0\nOnlyBoth cuts through it.\nThis benchmarking engine uses discovery algorithms to ferret out unique aspects of persons, places or things in a data base; compares them to others in the data base; then describes results in natural language. OnlyBoth is the AI-brainchild of Raul Valdes-Perez and Andre Lessa. They developed the discovery algorithms by studying the logic of certain tasks and noting which heuristics led to the best solutions.\nAs unique in its construction as it is in its ability to associate and assemble facts, OnlyBoth has analyzed \u2013 and written up \u2013 federal data from 4,813 American hospitals. Going to the OnlyBoth site, I learned that St. Agnes of Fond du Lac, WI, \u2013 compared to 14 near-by hospitals \u2013has the lowest spending per Medicare beneficiary, yet achieves the:\n\nlowest rate of unplanned readmission for chronic obstructive pulmonary disease (COPD) patients (18.8%);\nlowest acute myocardial infarction 30-day readmission rate (15.5%);\n2nd-lowest pneumonia 30-day mortality rate (11%); and\nlowest death rate for stroke patients (15.2%).\n\nTwenty-six other distinctive facts awaited my click, each one culled and written by AI software, ready to be presented in a fraction of a second.\n OnlyBoth \nBenchmarking is nothing new.\u00a0 Googling the term renders 25.5 million hits.\nCompanies use benchmarking to \u201ccompare key metrics to other businesses\u2026to see how well they are performing and identify ways they can become more competitive in the industry,\u201d according to Study.com. Its current practice, however, is complex, expensive and time-consuming; limited in scope; and constrained in economic value, according to Valdez-Perez. Automation is the solution, he says.\n\u201cJust like \u2018library search\u2019 engendered \u2018search engines\u2019, we aspire to have \u2018business benchmarking\u2019 lead to \u2018benchmarking engines,\u2019\u201d Valdes-Perez told me.\nAt the core of this engine is a compatriot to the \u201cIf\u2026then\u201d statement \u2013 the \u201conly..both.\u201d It combines two numeric attributes, Valdes-Perez explained: \u201cOnly P has both as much (or little) A and as much B.\u201d\nIn the hospitals data base, this statement plays out as: \u00a0\u201cOnly Meriter Hospital in Madison, WI has both as low an acute myocardial infarction 30-day mortality rate (11.4%) and as low an acute myocardial infarction 30-day readmission rate (16.2%).\nAnd it is, of course, also the basis of the company\u2019s name.\nTo appreciate the engine\u2019s potential, consider the background of Valdes-Perez and the man who mentored him. \u00a0Valdes-Perez, a PhD student at Carnegie Mellon University and later a CMU faculty member, co-founded a search software company, Vivisimo, which was sold to IBM in 2012. His advisor at CMU was Herb Simon, 1978 Nobel laureate in economics and recipient of the A.M. Turing Award and National Medal of Science.\nValdes-Perez distilled their time together into Personal Recollections from 15 Years of Monthly Meetings. Among the key takeaways from that publication: \u00a0the need for the right framework, when addressing a problem; what the answers to questions would look like; and ensuring that people will care about the result. \u00a0Each was considered in the development of OnlyBoth, today a laboratory curiosity, but probably not for long.\n\u201cThe hospitals application is a public service and showcase,\u201d he told me.\u00a0 \u201cWe'll be launching another in September.\u201d\nValdes-Perez did not say what this new application would be, only that cloud-based services will be a great new playing field for automated benchmarking, across industries. Like the data it plumbs, OnlyBoth is all about the possibilities.\n\u201cIf data is available and if organizations want to know how they are doing, where they could improve, and what's best in class, then the engine will generate the answers,\u201d Valdes-Perez told me.\nOnlyBoth\u2019s ability to mine and present findings in natural language could be taken as, well, a bit threatening to professional writers. It does, after all, do what we do \u2013 find the significance of data and report it. But I\u2019m not worried.\nOnlyBoth can knife through a massive data base. It connects the dots nicely. And, yes, it draws insightful conclusions.\u00a0 But\u2026\nCan it come up with clever endings for its stories? Riveting questions that keep its readers hanging?