Geospatial AI for Forest Integrity

Carbon Watch

Linked satellite, drone, and ground-truth data into a carbon assessment engine with automated reporting.

AWS LambdaSageMakerPostGISRaster AnalyticsCloudWatch

Problem → Outcome

Architected a serverless, multi-hop pipeline across Lambda, SageMaker, and PostGIS to transform heterogenous geospatial data into carbon readiness assessments. Built observability around data quality, latency, and inference drift.

  • Unified ingestion for vector + raster layers with schema validation and metadata lineage.
  • Deployed inference endpoints with canary rollouts and automated retraining triggers.
  • Delivered executive dashboards with live KPIs for forest health and carbon baselines.

Impact Metrics

↓ 63%Latency
↓ 42%Ops Cost
24+Automations
Read in Résumé