Mireye

/use-cases/insurance

Insurance underwriting

Wildfire + flood risk underwriting with per-field federal-source citations.

​ The query

cURL
curl -s https://api.mireye.com/v1/fetch \
  -H "Authorization: Bearer $MIREYE_API_TOKEN" \
  -H 'content-type: application/json' \
  -d '{
    "lat": 46.6,
    "lng": -93.7,
    "preset": "wildfire_underwrite"
  }' | jq

​ The response

JSON
{
  "lat": 46.6,
  "lng": -93.7,
  "fetched_at": "2026-06-12T07:28:11.332523+00:00",
  "fields": {
    "lcms_class": {
      "value": "Grass/Forb/Herb",
      "unit": null,
      "source": "USFS_LCMS",
      "source_url": "https://developers.google.com/earth-engine/datasets/catalog/USFS_GTAC_LCMS_v2024-10",
      "confidence": "high",
      "fetched_at": "2026-06-12T07:28:08.687077+00:00",
      "dataset_vintage": "2025-11",
      "ttl_seconds": 2592000,
      "notes": null
    },
    "tree_canopy_pct": {
      "value": 0.0,
      "unit": "percent",
      "source": "USGS_NLCD_TCC_V2023_5",
      "source_url": "https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_TCC_v2023-5",
      "confidence": "high",
      "fetched_at": "2026-06-12T07:28:11.331689+00:00",
      "dataset_vintage": "NLCD TCC 2023",
      "ttl_seconds": 2592000,
      "notes": null
    },
    "ndvi_current": {
      "value": 0.18159930408000946,
      "unit": null,
      "source": "COPERNICUS_S2_SR_HARMONIZED",
      "source_url": "https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED",
      "confidence": "high",
      "fetched_at": "2026-06-12T0

​ The audit trail

​ Adding flood

curl -s https://api.mireye.com/v1/fetch \
  -H "Authorization: Bearer $MIREYE_API_TOKEN" \
  -H 'content-type: application/json' \
  -d '{
    "lat": 46.6,
    "lng": -93.7,
    "preset": "flood_risk"
  }' | jq '{fields: (.fields | {elevation, intersects_wetland, wetland_type, wetlands_within_500m_count}), partial_failures}'

​ Why this works for insurance

  • Defensible. Every value cites the originating federal agency. The underwriter never has to defend a proprietary “model says 18%” number.
  • Reproducible. fetched_at plus source_url means a regulator three years from now can re-fetch the same source and confirm what was used at underwrite time.
  • Honest. When a source fails (cloudy Sentinel pass, EIA pipeline data lag), the failure surfaces in partial_failures with a retryable flag rather than silently substituting a stale value.
  • Composable. The carrier’s own scoring model lives on top — Mireye provides the inputs with provenance, the carrier’s actuaries weight them. The audit trail is preserved end-to-end.

​ What it does NOT do

  • Not a CAT model. Mireye returns the input data; modeling loss probability is the carrier’s job.
  • Not a parcel-search service. Geocoding from address to lat/lng is the caller’s responsibility (US Census Geocoder is free and works).
  • Not real-time event data. No active fire perimeters, no current flood gauge readings. Add those alongside via NIFC / USGS Water APIs if your underwriting requires them.