Netflix’s first Brazilian original production, an 8-part sci-fi thriller series titled 3%, is the streaming platform’s first original series filmed by, produced by and starring a cast of entirely Brazilians.

The first season of the series premiered to rave reviews on Netflix worldwide on November 25, 2016. And now the streaming platform has set a second season of 3%, announcing in a new teaser trailer that it will premiere on April 27.

3% is set in a dystopian future Brazil that exists between progress and devastation. Brazil’s surviving population live in a zone called Inland, which lacks energy, food and water. At the age of 20, everyone is given one chance, and one chance only, to apply for something called The Process, whose approved candidates get to live in Mar Alto, a utopian world. But only 3% of applicants actually are selected from all of those who go through The Process — hence the show’s title.

With a diverse cast of characters, 3% addresses social justice issues, like the gap between the established elite (as well as the power the wield) and the poor, spotlighting one of the most unequal societies in the world in Brazil. The 3% who are selected after going through The Process are defined in part by their attitude towards hierarchy and working together. Rafael is a pure egotist; Marco is a natural-born leader who doesn’t like his leadership questioned; Joana grew up on the streets and believes in the survival of the fittest; and wheelchair-bound Fernando believes blindly in the system. Asking the question, “if given the chance to live a better life, how far would you go for it?, ultimately, the series questions the dynamics of society that imposes constant selection processes we all have to go through, whether we like it or not. It’s definitely worth a look if you haven’t streamed season 1 yet.

Created by Pedro Aguilera, 3% is set up at Sao Paolo’s Boutique Filmes.

The inclusive cast includes Joao Miguel, Bianca Comparator, Joana Coelho, Zeze Motta and many others.

First full look at Season 2 below: