benshi.ai
our story
After working together for five years in Japan, focused on personalization in the video game industry, the founder and executives of benshi.ai decided to join forces with the Bill & Melinda Gates Foundation to ensure that the benefits of artificial intelligence, adaptive interventions, and data-centric technologies reach the most under-served communities worldwide.
The people at benshi.ai realize that the next revolution in healthcare will not be a drug or vaccine, but instead, the improved engagement of patients and providers to enhance relevant skillsets and quality of care.
benshi.ai is growing rapidly, with members from across the world supporting our mission of transforming global health with engagement-enabling technologies, to eliminate inequities in healthcare.
Founder and CEO África Periáñez joins forces with the Bill & Melinda Gates Foundation to ensure that the benefits of artificial intelligence, adaptive interventions, and data-centric technologies reach the most under-served communities worldwide.
Our work "Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs" together with Maternity Foundation, receives the best paper award at the KDD 2022 Workshop on Applied Data Science for Healthcare
Our papers, "A Data-Centric Behavioral Machine Learning Platform to Reduce Health Inequalities" and " A Recommendation System to Enhance Midwives' Capacities in Low-Income Countries" are accepted to NeurIPS 2021
benshi.ai launches its Android SDK to organize and label users logs and track time varying personalized behavior
The first version of benshi.ai’s machine learning platform to predict individual behaviors and deliver personalized nudges is deployed and ready for operational integration
Our paper "User Engagement in Mobile Health Applications", describing our research with Maternity Foundation, is presented at the 28th ACM SIGKDD Conference in Washington D.C.
Adaptive experimentation based on reinforcement learning (RL) is operationalized through our collaboration with SwipeRx to recommend the right drug to every pharmacist. To the best of our knowledge, this experiment represents the first attempt at implementing production RL in Global Health through mobile apps
