 Social risk and social listening, which I would rephrase as a social understanding, which is a little bit further, are related to collecting data about what people are saying, so collecting people's voices, in our case under an ethical way. So we respect the privacy and we aggregate all the data so no one can be punished for what they are saying. And in this case, what we are doing is collecting millions of voices in real time from multiple public data sources. So we can provide insights, like for example, emerging trends in social behavior or real needs related to hunger or what are the effects of natural disaster in real, so we collect that data in real time. So we can provide information, actionable information to our partners and our customers so they can react like much more faster and much more efficiently and they can generate like a more efficient impact in the society. We have an ongoing project called EARS with World Health Organization. In this case, we are collecting data worldwide about misinformation narratives around COVID and around vaccines. So we collect data and in this case, we are identifying narratives that are impacting in society related to so mainly vulnerable communities that get the COVID due to misinformation. As an example, in Colombia, we identified that there was like a narrative, a gender narrative related to fertility and getting vaccinated. And this was a growing belief within different communities. So after extracting this insight, the Ministry of Health can react and can inform better the population about which are the effects and the non-effects of getting vaccinated. We are in one of the most, it's not the worst pandemic but it's the most impactful pandemic probably. What we are seeing is that there is a huge problem of infodemia worldwide. So in the last two years, 90% of the data of Internet has been created and 80% is unstructured. So there's a lot of information and no one knows how to unlock the quality or the value of this information. So setting the standards, collaborating together in order to be able to help society within this context is super important and I think that this event is what I aim to do. Given this context of infodemia, data is heterogeneous and the quantity is growing exponentially. So it's really difficult to identify which data sets, which data sources are meaningful to understand and to be representative in taking conclusions about the problem. So these are the main challenges and then structuring that and structuring data and extracting relevant insights, not only anecdotic insights, I think it's the magic behind the technology. In our case, we work with public data sources or data sources that the people gave consent in order to be used. But in any case, we are not storing any personal data, we are aggregating all the data and all the information is even revised so we cannot track any individual. So all the insights are aggregated and I think that's also one of the magics of the technology behind this.