80%
Completeness rate
×2
Productivity gain
50+
Indicators tracked
Context
CDC Biodiversité develops the Global Biodiversity Score (GBS), a reference tool that enables companies and investors to measure their biodiversity footprint.
To feed its calculations, the organization relies on a large volume of financial and environmental data published by companies. This data comes from multiple formats and sources - CSRD, TNFD, TCFD, DPEF, and sustainability reports - making collection and harmonization particularly time-consuming.
CDC Biodiversité wanted to test automating this collection with Opale, to assess how AI could facilitate structuring, verifying, and updating the data used for biodiversity footprint measurements.
Approach
A pilot was conducted with Opale on a sample of 10 international companies (Europe, Asia, Latin America) across sectors: pharma, energy, real estate, industry, and automotive.
Documents were analyzed automatically to:
- Identify sections containing target data (revenue, converted areas, locations, water volumes, material tonnages, water/climate/biodiversity targets)
- Extract and structure values relevant to biodiversity analyses (GBS footprint measurement, location analysis, risk assessment)
- Associate each data point with its verifiable source, ensuring complete traceability
The entire process took place within Opale Grid, the collaborative environment that transforms large document volumes into analysis-ready databases.
The work with Opale was very smooth and efficient, with regular back-and-forth to refine prompts and improve performance. Result quality increased significantly within a few weeks. This co-construction produced reliable results on complex quantitative and qualitative indicators.
Lise Quenet
Research Analyst, CDC Biodiversité
Results
The pilot validated the reliability and performance of the automation:
- 80% overall completeness rate on tested indicators
- Analysis time halved compared to manual processing
This experiment demonstrated that a well-structured AI approach can make collection more reliable, improve sector coverage, and accelerate analysis while preserving source transparency.
Next steps
Encouraged by the pilot results, CDC Biodiversité is already preparing to scale up. In the next phase, the organization plans to use Opale to analyze biodiversity data from 60 major French companies based on their public data - automating collection and expanding the volume of companies analyzed with better-structured, traceable information.
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