Trustworthy AI · Independent R&D

MRV Forest Carbon QA System

An evidence-grounded environmental question-answering prototype designed around traceable retrieval, deterministic checks and reproducible deployment.

Period
2026–present
Status
Independent R&D prototype
Methods & technology
Python · RAG · Chroma · FastAPI · Docker · Automated testing

Problem

Environmental and MRV documents can be difficult to interrogate reliably when answers need traceable evidence and numerical consistency.

Context

This independent prototype explores how evidence-grounded retrieval and deterministic checks can improve environmental question answering.

Approach

The system uses provenance-preserving document processing, parent-child chunking, retrieval, metadata filtering, source traceability and output verification.

My role

I independently designed, implemented, tested, documented and packaged the prototype.

Result

A reproducible prototype was tested across local and remote compute environments, with source traceability and deterministic verification integrated into the workflow.

Evidence

The public repository and evaluation summary will be added when the project is ready for release.

Potential applications

Forest-carbon MRV, environmental reporting, evidence review, policy-document analysis and research knowledge systems.