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How AI describes Bidgely

Data as of Aug 25, 2026 · Based on 3,181,687 AI responses across 10,525 prompts · See how Parse measures this

Bidgely logoBidgelybidgely.com

Bidgely uses patented disaggregation technology to identify individual appliance usage within homes and businesses solely from meter data, requiring no additional hardware or customer action. The platform provides energy insights and analytics based on this foundational disaggregation data.

Parse Score

51.5

#92 of 142 in Smart Grid Management Platforms

Strength15
Reach39
Authority33

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Sources

bidgely.com shapes more of what AI says about Bidgely than any other source, at 48% of its citations.

utilitydive.com · worldmetrics.org · alectra.com · aws.amazon.com

AI questions where Bidgely appears

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The market map

Smart Grid Management Platforms →
2%5%10%20%50%Category leadersSpecialistsIn the mixLong tailNamed in more AI answers →Appears earlier in the answer →Schneider ElectricSiemensEnelUplightGE VernovaHoneywell HomeABBEatonCPower EnergyVoltusTeslaOracleEnergyHubEnersponseBidgely

Where AI ranks Bidgely

Smart Grid Management Platforms#92
#46

  • Excerpts where Bidgely appeared in the AI's answer

    ChatGPT Search · excerpt
    Bidgely — Provides AI energy analytics for utilities, including load insights from smart meter data and customer-level energy intelligence.

  • Excerpts where Bidgely appeared in the AI's answer

    Google AI Mode · excerpt
    Bidgely: Offers an agentic AI layer designed for utility grid planning.

  • Excerpts where Bidgely appeared in the AI's answer

    Google AI Mode · excerpt
    Bidgely Integrated Grid Planning (IGP): Uses behind-the-meter data analytics for scenario planning and granular demand forecasting

  • Excerpts where Bidgely appeared in the AI's answer

    ChatGPT Search · excerpt
    Bidgely — analytics-driven targeting (identifies best DR participants using AMI data)

  • Excerpts where Bidgely appeared in the AI's answer

    Google AI Mode · excerpt
    Bidgely : Uses patented AI disaggregation to extract granular insights