We make carbon measurable, mappable, and real.
A carbon-monitoring platform needed to turn millions of land parcels and time-series measurements into decisions and reports stakeholders could trust. We designed, built, and now operate the interactive geospatial analytics platform behind it — from raw boundaries to sub-five-second insight.
Trustworthy insight across huge geospatial datasets — in one unified system.
ESG, carbon, and land-management platforms live or die on whether their numbers hold up. The value we delivered is not a dashboard; it is a foundation stakeholders can audit and defend.
Trustworthy insight at scale
Complex aggregations across millions of land parcels resolve in under five seconds — fast enough that analysis becomes a conversation, not an overnight batch job.
Unified system, no drift
Transactional writes and heavy analytical reads share a single database. No separate warehouse, no sync latency, no divergence between what you record and what you report.
Multi-tenant SaaS by design
Strict account-level isolation and automated onboarding. Every tenant sees only their own estates, farms, and management units — reproducible and secure.
A defensible history
A time-aware model records every land-use change, so any parcel can be queried exactly as it stood on any date. Stakeholders get numbers they can trace and defend.
Net ecosystem exchange, tracked month over month.
Every parcel carries its own time-series of NEE measurements. The platform renders them as monthly and annual trends against a fitted baseline — so a change in practice shows up as a change in the curve, and a carbon claim can be traced back to the measurement behind it.
The engineering that makes geospatial analytics fast — and defensible.
Four decisions carry the platform: index on the ones that matter, keep the jargon purposeful.
Interactive map-based analytics
A full ArcGIS visualization layer for plotting and managing parcel polygons directly on the map — draw boundaries, filter by attribute, group by tag, and read carbon metrics in place instead of scrolling spreadsheets.
Geospatial · Polygon plotting · In-map filteringTime-aware EAV data model
An Entity-Attribute-Value model captures the full history of every polygon — attributes, practices, and land-use change over time. Land-use change is a first-class query, not an afterthought.
EAV pattern · Historical tracking · VersionedOne database, two workloads
A single Aurora Serverless v2 (PostgreSQL) foundation serves transactional queries and analytical aggregations alike — accessed over the RDS Data API with no connection pooling to manage.
Aurora Serverless · Unified · Zero-syncServerless, isolated, reproducible
Chalice, Lambda, API Gateway, S3, CloudFront, and Cognito — pay-per-use and automatically scaling. Cognito, JWT, and CloudFormation-defined infrastructure make every environment reproducible and secure.
Cognito · JWT · Infrastructure as codePolygons in. Decisions out.
Raw boundaries and time-series measurements flow into a single serverless core, then out to an interactive, multi-tenant map dashboard — no separate transactional and analytical stacks to keep in sync.
The stack, stated plainly.
Bring us the geospatial problem that sounds too tangled to unify.
Carbon data is complex, spatial, and time-bound — and so is our engineering. We have already shipped the trustworthy, auditable, real-time platform this space demands. Let's build yours.