Instantly assess your ESG risk exposure and centralize your CSR and ESG actionsBook a Demo
ESG assessment & monitoring for Supply Chains
Reporting on major ESG risk-exposure in specific industries and products using the FINGREEN Sentinel tool
ESG data room for instant communication with investors
work with company that has
strong environmental policies
into supply chain criteria
Our programming language developed in-house by our experts to translate and automate 20+ ESG standards and frameworks.
Explainable Artificial Intelligence
Innovative AI technology designed to enable full transparency and traceability.
Fraud detection system to ensure every declarative metric is thoroughly checked.
How can I use FINGREEN AI?
To see how our platform works, you can book a demo directly by clicking the “Demo” button on the top right of the page. You can also subscribe to our newsletter or reach us on LinkedIn
What is FINGREEN AI ?
FINGREEN AI is a SAAS platform that provides all-in-one ESG data services from collection and analytics to insights and reporting. We also provide custom services to develop tailor-made solutions according to your needs and requirements, such as detailed ESG due diligence or industry-specific ESG risk exposure.
What do you mean by FINGREEN AI Methodology?
With ESG metrics based on the aggregation of 10+global ESG standards, frameworks and scientific-based methodologies, we provide automated alignment and reporting with 100% traceability.
What is your pricing?
We have different pricing for different use cases and features. Before officially subscribing to our platform, you can order a Proof of Concept (PoC). Contact us to book a demo in order to know more!
Can you customize based on my needs?
Definitely! We are flexible in configuring the FINGREEN AI tool to help you reach your specific goals.
How do you ensure data quality?
ESG data is the base of everything we do so we want to make sure we have impeccable data availability, standardisation, quality, traceability and transparency:
1) FINGREEN AI proprietary data sourcing from public data sources
2) Explainable AI data estimation models
3) Engaging and guided process for data collection.