SAV AI · Using AI & Blockchain to Combat Human Trafficking in Kenya | Pitch Presentation
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0:00AThere is a rise in human trafficking in Kenya, mostly sub-Saharan Africa. Why is that possible? Is because Kenya is like the middle hub of the airlines. So we have most people coming in from low-income areas being trafficked through to the Saudi Arabia, those Middle East countries. So a report done by the United Nations Office of Drugs and Crime shows that in Kenya, mostly sub-Saharan Africa, they had human trafficking of 74 victims as of last year. So Kenya Airways partnered with UNODC to combat this crime, but still they were not able to be successful. Why is it possible? Because they, they had like, they trained them the airport staff to track this. So why we need SavAI? SavAI comes in into being able to employ AI and blockchain for human surveillance and reduce this. So we’ll go and look into the key features.
1:07BOK, so we have 5 key features. The first one is AI-driven automation detection of crime. Scans, it can scan facial movement, body movement to detect and predict crimes. Next thing is tamper-proof footage storage, and it will be stored on the blockchain system storage. Another one is automated security alerts. So just like normal, normal, the word is gone. Yeah, normal security CCTV systems. This will be more advanced for giving description of the criminal that’s committed the crime. Then multi-tracking system -- multi-camera tracking systems to have different points of views of the crimes. Then general data protection regulation and data compliance. So we’ll have law enforcement to help make that work well and be transparent. Next slide.
2:08ASo this --
2:12BYeah. This is a photo example of how our site looks like. If you click on the logo, you can get more info and go to the site. This is just a shortened version of what I’ve just talked about. Next slide. Our target users are airports, ports, and train stations because they have high-traffic areas and humans. Other CV areas would not really be as effective as AI systems. Next slide. So this is a rising -- it’s a rising demand, not only in Kenya, but globally, because the billions of dollars that the Kenyan government can invest into the systems. And also globally, there’s a huge return of investment within the next, what, 4 years?
2:54AYeah.
2:55BAnd we have the potential to expand to other markets apart from airports, train stations, and ports. We can also go to casinos and smart cities. Next slide. This is our 3-week roadmap. So far, we’ve done some AI data training. We’ll continue the rest.
3:17AYeah.
3:17BThen possible challenges. Should I hand it to you?
3:21AYeah, just hold it.
3:22COK. For the possible challenges that you may be able to experience, we have data privacy concern. So here, we have to put into consideration the GDPR and the Kenya Data Protection Act. Because we understand that is the ultimate currency, so we need to take care of the data that we’re going to collect. And then we have AI bias and false positives. So here we have to use AI in an ethical way. So that is something we also put into consideration. And then hardware compatibility. So what’s good about software if it can’t be able to be integrated correctly with the hardware? So that is -- we are going to use existing system.
3:22CWe’re not going to do something like from scratch. But we just want to enhance the systems. And then adoption barriers. Yeah, so this convincing organizations, so that is going to also take us some time to be able to convince various, maybe governments or enterprises, to be able to switch from the traditional way to this other way. And how we compare to Avigilon. So these are one of our competitors. Again, these guys are using the cloud storage, which is more expensive and slow access. And as for us, we’re going to use decentralized storage, which will be Storj. And then we have -- we are going to focus on -- OK, for them, they’re focusing on fixed security solutions.
3:22CBut for us, we have predictive analysis, anomaly detection, and proactive security. It requires significant manual monitoring, which leads to delay in the process. But for us, we’re going to integrate AI into our system.
4:50ASo --
4:53BI’ll be brief, so we won’t go into this in detail, but you’ll have access to the slides at the end. But we have per camera packages and monthly packages. Next slide, please. Our ask is strategic partnerships with our target markets, legal expertise, because none of us are lawyers, so we don’t know how to deal with the AI regulations, funding -- that’s our estimate -- incubation from LISC and AYA kindly, and mentorship from Invisible Garden for the AI section. Next slide, please. This is our team. Next. Do you have any questions?
