Natural Language Processing at City-Zen AI: How machine learning could transform citizen/welfare services

 

We use Machine Learning algorithms to model and enable the analysis of large unstructured natural language datasets in the form of free-text statements from the public. 

 

The CIty-Zen AI API then triages, logs and categorises the information before passing it to the correct delivery provider, department or source of help. 

 

This is achieved by NLP to allows for geolocation/ subject matter sorting, sentiment and structural analysis to be able to assign cases to the right places/people every time. 

Key Objectives:- Prioritise - To use the AI Machine Learning Technology to;

  • Capture and prioritise the requests from Care and Key workers by the Council and Clinical Commissioning Groups (CCG).

  • Relieve pressure on currently seconded DWP staff to local authority call centres and others.

  • Help communicate and contextualise the current status of people who fall into the UK's 1.5 million shielded most vulnerable people.

  • Increase productivity of Councils and CCG other staff by reducing repeating tasks and firefighting increased call volumes.

  • Help Councils model and mitigate risk on vulnerable /shielded people due to the compound impact of a secondary disaster such as act of terrorism or an extreme weather event like flooding,

  • Increase Councils and CCGs data-fluency rates by augmenting their Data Science, AI Machine learning ability and expertise.

  • Create predictive analytics to help Council and CCG officials make better-informed decisions city strategies.

  • Meet the demand for services as our cities as the UK potentially become vulnerable to increasing deprivation.

  • Work with Councils to compliment their own tech infrastructure.