ReportGRI: Automating GRI Alignment and Report Assessment

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Welcome to the ReportGRI project repository. This tool provides easy visual analytics for corporate sustainability reports (CSRs) based on Global Reporting Initiative (GRI) disclsoure requirements. The reports are checked for GRI disclosure completeness and materiality and receive GRI indexing suggestions. As part of this project we are primarily focusing on: Standardising unstructured data from CSRs, Creating environemntal, social, governance (ESG) benchamrking and Generating LLM-based assessment of report coverage.

Main features of ReportGRI include:

• GRI disclosure-paragrph distribution of reports
• Report topical focus with respect to GRI standard topics
• Disclosure assessment for completeness and materiality
• Upload your report to view the GRI distribution and do comparative analysis with industry peers, and receive LLM-based indexing suggestions

(The deployed version could be tested on https://reportgri.nliwod.org/)

📣 Paper got accepted to CIKM 2025 Demo Track!

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Installation and Setup

Prerequisites

• Node.js (>=18) and npm
• Python 3.10+ with pip
• Docker + Docker Compose (optional for Docker setup)

Clone the repository

git clone https://github.com/aidausmanova/reportGRI.git
cd reportGRI

Environment setup

cd backend
conda create --name reportgri python=3.10
conda activate reportgri 
pip install -r requirements.txt

To test pipeline only, add your report in PDF format to data/original/ and run the script with your report name specified in run_test_pipeline.sh.

bash scirpts/run_test_pipeline.sh

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Backend Setup (FastAPI)

Run FastAPI

uvicorn main:app --reload

Server will start at: http://localhost:8000

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Frontend Setup (React 19 + TailwindCSS)

Install Frontend Packages

cd frontend
npm install

Run Vite Dev Server

npm run dev

Frontend will start at: http://localhost:5173

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Optional: Docker Setup (Combined)

Build and Start All Containers

docker-compose up --build

Backend on http://localhost:8000
Frontend on http://localhost:5173

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Note

To use gpt-3.5-turbo-1106, create .env file and add your api key as in the example below:

OPENAI_API_KEY=<Your OpenAI key>
BASE_URL='https://api.openai.com/v1'

Citations

@inproceedings{usmanova2025ReportGRI,
    title = {ReportGRI: Automating GRI Alignment and Report Assessment},
    author = {Usmanova, Aida and Abdullah, Rana and Banerjee, Debayan and Leippold, Markus and Usbeck, Ricardo},
    year = {2025},
    isbn = {9798400720406},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3746252.3761469},
    doi = {10.1145/3746252.3761469},
    booktitle = {Proceedings of the 34th ACM International Conference on Information and Knowledge Management},
    location = {Seoul, South Korea},
    series = {CIKM '25}
}

Thank you for your interest in our project! We hope you find this repository useful and informative.