Principal Investigator: Jae Lee (Business and Information Systems Undergraduate/SMU and SUTD)
Team: Olivia Low (Human Resources Management and Services Undergraduate /NTU)
Mentor: Gustavo Liu (Founder/EAT Launchpad)


Analyzes publicly available information sources to obtain sentiment scores on companies

Huuve analyzes publicly available information sources to obtain sentiment scores on companies. These scores are used for information gathering or trading purposes. Huuve's strength lies in its proprietary semantic tagging models that enable rapid identification of companies that could be affected by a particular information item, on top of its information gathering infrastructure that enables low-latency dissemination of information to our clients.

Huuve utilizes artificial intelligence appropriately. Specifically, in syntactic, semantic and sentiment tagging which encompasses both supervised and unsupervised learning methods within the Natural Language Processing (NLP) space.

To suit the needs of clients, Huuve provides varied forms of access to clients, including via an API, a dashboard and spreadsheets. At the same time, Huuve writes whitepapers to showcase examples of potential alpha generation using sentiment scores, so as to give confidence that they too can do something similar.