Informal Jobs Statistics
Find a decent job!
Inspiration Ana is a single mom from Santiago, Chile, that walks every day multiple miles trying to find a decent job... And this story, repeats daily, across our Latin Countries.
According to the United Nations, 2/3 of human population are part of the informal economy. Just in Latinamerica, the International Labor Organization estimates there are 140 million persons in this situation.
What it does Through the FB Messenger, we allow the users to connect and create with decent jobs opportunities. The payment suggestion as a 'decent job', is based on the references of variables like minimum salaries per region and job, so with this we can help to close the asymmetry of information between the parts.
How we built it We create a virtual agent for FB messenger, that integrates with APIs for NLP recognition, so that the assistant can identify actions and map references values from the conversations, and then we apply different services for the tool like getting user location through the messenger and handling pictures as responses on the dialogue, so the persons can create jobs opportunities in the platform. Finally, users can connect with jobs opportunities based on their skills and locations.
Challenges we ran into Many... We had to pivot the idea a couple of times, mainly because of technical restrictions in some of the products or even data regulation compliance.
Also another big challenge we had, is to adjust an accurate a model that provides a real and efficient pricing reveal by job, skill & location.
Accomplishments that we're proud of FB Messenger Bot Live: m.me/kaziassistant
What we learned That when you can identify a huge problem impact, and yes you can do something about it, that we are living a historical moment were nowadays people exchange billions of messages through FB Messenger, so that the impact and scalability of the solutions
What's next for Kazi Assistant More Learning opportunities + step by step on getting or improving your skills for your interests + adjusting the pricing data model and