starseed brand monitoring

Starseed AI's real-time ready-to-download EMV reporting quiets the noise and presents data and insights that matter to rights holders and brands.


By analyzing millions of worldwide online conversations in 50 languages, Starseed AI uses its patent-pending semantic AI and analytics algorithms on big data (Web 2.0 data) to identify the real-time Earned Media Value (EMV) of sports and entertainment brands beyond the traditional channels.

The Next Gen AI For Real-Time Audience Measurements & Sponsorship Earned Media Valuation (EMV)


Starseed AI is a patent-pending and real-time brand detection system that can quickly and with high accuracy identify logos, text, scenes, and mentions of your sponsors brands in any images and videos or textual descriptions/mentions.



Image Visual & Textual EMV Monitoring


Starseed monitors social media, blogs, website all in real-time.



Image For Rights-holders (Teams, Leagues)
Image For Brand & Sponsors
Image For esports (Teams, Broadcasters)
Image

Fastest Growing Datasets Powered by Patent-Pending AI Tech


Starseed AI state-of-the-art, real-time and historical data sets can track back all the way to 2006.


Image Historical Datasets

1.7 trillion historical conversations back to 2006 (Except for TikTok)


Image Real-time Datasets

500 million new conversations added every day


Image Diverse Datasets

Conversations from 100 million unique sites and billions of sources including Twitter, TikTok, Instagram, Facebook, Reddit, Blogs and websites


Real-Time Global Audience Intelligence & Insight From West to East


Starseed AI state-of-the-art, real-time audience analysis has the inside track on audience data, meaning you get a peek inside how they are, where they are from, what languages they speak, what level of income and education they have, what is their media behavior, brand attributes and purchasing habits, and demonstrates how these factors impact sponsorship decisions.


Image Real-time Socio-Demographics

Salary & Income
Geo-location
Gender
Spoken Languages


Image Audience Interests

Consumer Segmentation
Affinities
and Interests