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import groundswell as gs
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local_exposure_data = gs.connectors.load_local(
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path="data.csv"
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)
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result = gs.workflows.run(
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"RiskAssessment",
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model="gemini-2.5-pro",
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data_sources=["NOAA", local_exposure_data],
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location="Copenhagen",
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scenario="SSP2-4.5",
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)
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print(result.assessment_summary)
Easily connect your enterprise data to Groundswell with our Python SDK. Our AI agents help you fill in the gaps.
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Plan warehouse and factory retrofits—passive cooling, shade, and shift scheduling—to reduce heat exposure while maintaining throughput. Estimate cost and impact.
Screen municipal and corporate projects for adaptation outcomes, quantify benefits, and package them into investable portfolios with measurable KPIs.
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