ISS CROSS-BORDER CHILD PROTECTION

Background Information

Client: International Social Sevice (ISS)

Skills and Proficiency: Python, Flask, Model Deployment on Heroku, Natural Language Processing, Problem Scoping.

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Problem: 

• Harness the potential of the underlying gold mine of expert knowledge

• Relieve the limited staff of repetitive administrative and operational task

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Process: 

In a collaborative effort, our team searched the web and collected more than 230 publicly available cases on child protection and abuse.

In the next step, the team applied various Natural Language Processing (NLP) techniques to make the data usable.

Finally, our team built an easy-to-use web application that displays case types, keywords, similar cases, a risk score, and more.

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Result:

With the help of the AI-powered tool, caseworkers can now familiarize themselves with cases more quickly – and have the experience of their colleagues around the world at their fingertips.