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How Jewelers Mutual uses H2O.ai

ConfirmedVendor case study · Checked Oct 29, 2026
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The use case: how Jewelers Mutual deploys H2O.ai

Jewelers Mutual, an insurer dedicated to jewelry, uses H2O Driverless AI and H2O-3 to build explainable machine learning models that give commercial underwriters reason-coded decisions through a web application. The models are deployed as MOJOs across a hybrid cloud environment and also help identify jewelry stores needing extra physical security during wildfires and power outages.

In the customer’s words

We chose H2O AI because it gave us the transparency we needed into our machine learning process, much more flexibility than the other tools we evaluated, and the strongest machine learning explainability capabilities on the market.
Andrew Langsner, Senior Manager, Embedded Analytics at Jewelers Mutual — Source

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Based on H2O.ai’s published case study. We check the public evidence; the results are reported by the vendor.

h2o.ai
Last checked
Oct 29, 2026
h2o.aiCaptured H2O.ai case study about Jewelers MutualOpen source capture
What the story claims, and what we checked

What we compared with the page.

  • The passage quoted aboveChecked

    Copied word for word from the page, near the name of Jewelers Mutual.

  • The numbers in our summaryChecked

    Each one is printed on the page.

  • Jewelers Mutual uses H2O.aiChecked

    Confirmed line.

  • The result itselfNot checked

    We quote it; we did not measure it.

With explainable models in production, Jewelers Mutual offered more competitive jewelry protection rates and improved its overall business relationships with jeweler partners.
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