sa TLDR | Messapps

TLDR

Category: Contestants

 

Name: Maxwell Kenzo Nakamura

NYU affiliation: School of Professional Studies

NYU status: Graduate

Did you enter last year?: No

Do you have any teammates?: Yes

How many, including yourself?: 3

 

Concept Name

TLDR

 

High Concept Statement

Using open source speech synthesis machine learning to read out loud curated editorials and articles that have been “saved for later” by users.

 

Status Quo

Most “read later” articles are never read.  Long form articles are highly engaging content yet, of course, take longer to read.  Commuting, driving, and other moments of ____ can be filled with things people want to read but don’t have time for.

 

Competition

Audiobooks and podcasts are competing for the same use cases, but distribute content different from what we would offer (audiobooks narrate books, podcasts are originally formatted for audio).  The reading of articles in their original format is also another form of competition to this idea.

 

Solution

We will provide a simple to use app that takes articles from common read-later services and serve made-to-order audio readings of those articles to users using speech synthesis technology powered by machine learning.  We will also offer curated selections of narrated articles from popular publications every day (perhaps from human-readers).

 

Revenue Model

We will have a tiered subscription freemium model for users of the service. We will have paid partnerships with publications that will provide them with more distribution in a different use case of content they already produce.

 

Which platform would you like to launch your app on?

iPhone

 

Which category best describes your app?

Utilities