Transform the way of your traditional environmental analysis with one of the world’s most advanced machine learning capabilities dedicated to environmental science

Key problems that we solve

Collect every piece of data you need to conduct environmental research

Streamline your analysis using our algorithm and free up manpower

Extract various sustainability commitments using advanced NLP algorithm

Tackle challenges from environmental analysis creatively using AI

Practical Case

How AI Supercharges Environmental Initiatives

Trusted by world leading environmental NGOs and research labs, we are constantly improving our methodology to help transform the traditional environmental analysis and drive societal impact

Our Services


From policy collection, key content identification, to document processing and tracking, we provide end-to-end service to free up manpower in analyzing environmental policies and legislations


As a key part of the process, we offer an automated pipeline to collect all the data needed to complete a Life Cycle Assessment and thus save the time and resources required


Build full-scale knowledge from multilingual sources for any environment or sustainability topics that effectively tackles the difficulty in data collection for environmental research


Tailor our proprietary algorithmic solutions and develop new technical processes to answer your research question with creative data-driven thinking

Why Work With Us


We possess a rare and unique combination of network intelligence and environmental science. We have a proven record working with industry leaders to apply data-driven thinking to solve environmental challenges


Our portfolio of algorithms can comprehend large amounts of unstructured data into meaningful formats, thus helping researchers significantly speed up their environmental research processes


We have a deep experience in empowering traditional research institutions with data science and automation. We are your to-go data partner that solves any challenges you are facing.