Facial Recognition

NuLabs developed a proof-of-concept solution to help a client check-in attendees faster and without having to provide a physical token or privileged information. The solution was developed for various devices such as Rasberry Pi, Android, and PC using Python and AWS Rekognition.

Natural Language Processing

NuLabs leveraged machine learning technologies to help a client build a proof-of-concept solution for extracting information from unstructured data sources. The NLP solution was built using technologies such as NLTK and Python.

Machine Learning

NuLabs used machine learning models such as Logistic Regression and KNN to help build a proof-of-concept solution for a customer to predict customer churn. The solution was built using Python.



Instantaneous check-ins at a large scale event through intelligent facial recognition.


A large event logistics provider in India was looking for alternative ways to improve and optimize the event check-in process which is usually cumbersome, time consuming and chaotic. The solution would need to provide a smart, easy and quick method to capture visitor check-in, making it a seamless end-to-end process while ensuring privacy of user information.