Meza is an artificial intelligence (AI) tool used to digitise paper records cheaply and quickly, using low-end smartphones.
Nutrition records for millions of malnourished children lie in remote health clinics around the world. This data is difficult to surface for officers designing nutrition interventions remotely. Getting the data to headquarters cheaply and quickly could improve the quality of our interventions.
Meza is an Optical Character Recognition technology to rapidly collect nutrition and related health data from remote, low-resource health clinics, enabling WFP and governments to have the information they need to provide high-quality, context-specific, and timely nutrition support.
A proof of concept pilot was run during the first half of 2022, validating the high accuracy of Meza’s transcription, in 94% of analyzed logbooks. A pilot was subsequently run in Rwanda where logbooks covering data of 2000 beneficiaries from 6 health clinics were analyzed through Meza and confirmed the high accuracy of the tool since over 98% of the data were accurately transcribed, proving the ability of the tool to reduce the reporting time that is currently taking months in many places to almost a real time availability of data.
