Why Can Citibeats’ Solution Impact Society?

Illustration of people walking in the city with Citibeats logo and text - Turn talk into action

In the era of Smart Cities, social media and the Internet itself offer a constant flow of people’s concerns and desires, a piece of information that can help decision-makers to act faster and more efficiently. People have become their vital core, but sometimes thousands and thousands of data can be difficult to read.

Citibeats is the fastest and most efficient social intelligence and speech analytics platform in the market. Based on natural language processing (NPL) and machine learning, Citibeats organizes unstructured data. Our platform allows for the gathering of relevant information in changing social contexts, which permits public organizations and financial institutions to react more quickly and efficiently to the needs of citizens.

How does Citibeat’s solution work?

The basics are simple: once the data is collected from different sources in any language, it’s then structured by custom AI models and analysed to be finally presented on visual dashboards that can be easily integrated on any workflow.
Sustainable development, financial inclusion, natural disaster response, social policy, hate speech policy, are only some of the areas where Citibeats’ solution can provide service.
With all of this in mind, how can we impact society through our solutions?
Citibeats’ was created as a social company. Through our journey, we have developed an ethical Artificial Intelligence designed to bring humanity back into decision-making, something that has been ignored for years. Our mission is to power a responsive society by distilling concerns and making them measurable.

A few examples

How is all of that becoming a reality? In only a few years of activity, Citibeats has joined forces with cities such as Dublin or countries like Japan or Kenya.
Through our projects, we’ve been able to give consumers a voice where there was none, we’ve improved natural disasters response by using people as a ‘sensor’ or we’ve taken measurements of gender and hate speech for creating better public policies.
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