News

Lost Town – new multiplayer gamebook fundrising campaign launched

The newly founded indie game developer FAR Entertainment Studio launched their first Indiegogo campaign and are now seeking support for their upcoming gamebook Lost Town. If successful, this sandbox multiplayer title will be available for Android, Amazon Fire (including Fire TV) and IOS.

screenshot2

Lost Town will be a non-massive multiplayer, asynchronous survival gamebook where up to 4 players (human or AI) can explore the town that went silent overnight. There will be 10 different characters (16 for the stretch goal) and at least 30 locations (or more) full of hazards, dangers, tools and clues that will reveal the terrifying truth about the Town and what actually happened. Each art_shipnew game will be divided into seven days with variable duration (set by players) where individual group members can explore the districts on their own. Once the day is over, the party will gather at their shelter where players can share their experiences, bringing the storyline closer to one of the possible endings. The game can also be played with AI controlled companions, but you will have to make all the night choices alone.

To animate the campaign, the developers from FAR decided to release weekly web episodes that will cover the background stories about six of the Town survivors, narrated by the company founder Fabio Andrea Rossi. This can be quite useful considering that some Town locations can only be visited if certain characters are included in the party.

Lost Town’s “Indiegogo” campaign set at €15,000 (about $20.500), was already launched yesterday. Supporters can choose the amount of money they wish to contribute, or select some of the predefined “perks” that will also yield adequate reward. To find out more and watch the first weekly episode (The Survivor), follow the link below.

Lost Town – Indiegogo project

 

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.