{
  "icp": {
    "use_cases": [
      "visual inspection data management",
      "predictive maintenance",
      "AI-based defect detection from drone/aerial imagery",
      "vegetation encroachment monitoring"
    ],
    "industries": [
      "power transmission and distribution",
      "wind energy",
      "solar energy",
      "buildings and real estate",
      "critical infrastructure"
    ]
  },
  "itha": "0.1",
  "proof": {
    "customers": [
      {
        "name": "Measure"
      },
      {
        "name": "Energinet"
      },
      {
        "name": "RPG Resources"
      },
      {
        "name": "Phase One"
      },
      {
        "name": "LINIA"
      },
      {
        "name": "Northern Powergrid"
      },
      {
        "name": "Statnett"
      }
    ],
    "case_studies": [
      {
        "url": "https://scopito.com/scopito-northern-powergrid-visual-inspection-data-management/",
        "title": "Northern Powergrid Selects Scopito to Modernize Visual Inspection Data Management"
      },
      {
        "url": "https://scopito.com/statnett-inspection-data-management/",
        "title": "Statnett Chooses Scopito for Advanced Inspection Data Management"
      },
      {
        "url": "https://scopito.com/ai-for-rust-detection/",
        "title": "A solid foundation. How a large utility deploys AI for rust detection"
      }
    ]
  },
  "company": {
    "hq": {
      "city": "Aarhus N",
      "country": "DK"
    },
    "url": "https://scopito.com/",
    "name": "Scopito",
    "domain": "scopito.com",
    "founded": 2014,
    "same_as": [
      "https://www.linkedin.com/company/scopito-aps"
    ],
    "employees": {
      "max": 50,
      "min": 11
    },
    "description": "Cloud-based visual inspection software that digitizes assets using automation and machine learning, applying AI fault detection to geospatial inspection imagery to support predictive maintenance for power lines, wind turbines, solar PV and buildings."
  },
  "offerings": [
    {
      "id": "power-line-inspection",
      "url": "https://scopito.com/power-line-inspection-software/",
      "kind": "software",
      "name": "Power Line Inspection Software",
      "terms": {
        "trial": true
      },
      "pricing": {
        "unit": "asset",
        "as_of": "2026-09-04",
        "basis": "list",
        "model": "usage",
        "notes": "Distribution poles: €10 self-analysis / €16 expert review. Transmission pylons: €20 self-analysis / €40 expert review. Enterprise and white-label (from €15,000) quoted separately.",
        "range": {
          "max": 40,
          "min": 10
        },
        "currency": "EUR"
      },
      "summary": "Cloud platform for analyzing drone/aerial imagery of power line poles and pylons, with AI fault detection, map-based geo-tagging, encroachment analysis, and SAP work-order integration.",
      "channels": [
        "direct"
      ]
    },
    {
      "id": "wind-turbine-inspection",
      "url": "https://scopito.com/wind-turbine-inspection-software/",
      "kind": "software",
      "name": "Wind Turbine Inspection Software",
      "terms": {
        "trial": true
      },
      "pricing": {
        "unit": "asset",
        "as_of": "2026-09-04",
        "basis": "list",
        "model": "usage",
        "notes": "Per turbine: €80 self-analysis, €160 expert review. Enterprise license with volume discounts and on-premise installation quoted separately.",
        "range": {
          "max": 160,
          "min": 80
        },
        "currency": "EUR"
      },
      "summary": "Cloud platform for analyzing turbine blade imagery, locating defects on a live turbine diagram with distance-from-root data, with AI fault detection and SAP work-order integration.",
      "channels": [
        "direct"
      ]
    },
    {
      "id": "building-inspection",
      "url": "https://scopito.com/building-inspection-software/",
      "kind": "software",
      "name": "Building Inspection Software",
      "terms": {
        "trial": true
      },
      "pricing": {
        "unit": "asset",
        "as_of": "2026-09-04",
        "basis": "list",
        "model": "usage",
        "notes": "Per building: €0 self-analysis, €50 platform analysis. Enterprise license (unlimited images, 1-year data access) quoted separately.",
        "range": {
          "max": 50,
          "min": 0
        },
        "currency": "EUR"
      },
      "summary": "Cloud platform for building and roof condition assessment from aerial imagery, with thermal analysis, historic comparison across repeat inspections, and AI fault detection.",
      "channels": [
        "direct"
      ]
    },
    {
      "id": "solar-pv-inspection",
      "url": "https://scopito.com/solar-pv-inspection-software/",
      "kind": "software",
      "name": "Solar PV Inspection Software",
      "terms": {
        "trial": true
      },
      "pricing": {
        "unit": "mw",
        "as_of": "2026-09-04",
        "basis": "list",
        "model": "usage",
        "notes": "Per MW: €0 self-analysis, €20 standard analysis, €65 full-service (10 MW minimum). Enterprise license quoted separately.",
        "range": {
          "max": 65,
          "min": 0
        },
        "currency": "EUR"
      },
      "summary": "Cloud platform for analyzing solar PV plant imagery per MW capacity, with thermal analysis, GIS baselayer support, and AI fault detection.",
      "channels": [
        "direct"
      ]
    },
    {
      "id": "other-infrastructure-inspection",
      "url": "https://scopito.com/other/",
      "kind": "software",
      "name": "Other Infrastructure Inspection Software",
      "terms": {
        "trial": true
      },
      "pricing": {
        "model": "quote"
      },
      "summary": "Visual inspection data management for cell towers, oil and gas assets, road and rail, bridges, and chimneys, using the same map-based, AI-assisted analysis and reporting platform.",
      "channels": [
        "direct"
      ]
    }
  ],
  "engagement": {
    "url": "https://scopito.com/contact-us/",
    "methods": [
      "quote_request",
      "trial"
    ]
  },
  "updated_at": "2026-09-04"
}