Scientific reference data
Digitized an extensive set of reference datasets (forest production species, wood densities, fire risk by region) with full versioning infrastructure.
CASE STUDY
How we designed and built an auditable calculation engine that translates a complex European carbon certification methodology from manual Excel models into a production-ready, API-first system.

The Challenge
An organization developing post-disaster reforestation projects needed to calculate and document the climate benefits of each project — how much carbon is stored or avoided relative to a baseline scenario — closely following a recognized European carbon certification methodology. Until then, the calculations were done in complex Excel models: a process that was hard to scale, error-prone, and lacked the transparency auditors and investors require.

Our Approach
infoteam took on the design and implementation of a backend calculation engine that translates the scientific methodology into production-grade code, built on three core principles: deterministic results, versioned reference data, and full compatibility with the existing reference tool. The core was built as a pure calculation engine (Spring Boot / Kotlin), with a full REST API secured through Keycloak, feeding an Angular frontend wizard.
Digitized an extensive set of reference datasets (forest production species, wood densities, fire risk by region) with full versioning infrastructure.
Biomass growth models, root system equations, product carbon-storage decay models, and conservative estimation logic.
Designed from day one with a strategy pattern, so new geographic regions with different equations can be added later without refactoring.
Every calculation stores a snapshot of its inputs and intermediate values, verified against Excel at every individual step.
The project is under active development, aiming to fully replace the manual process — with an API-first system able to support multiple concurrent projects.
Full transparency in the calculation methodology — a critical factor for the credibility of carbon credits with auditors and investors.