We Create Technology for a Better Life for Creators.
Glow.B leverages digital platforms and AI technology to address the financial accessibility challenges faced by creators. Unlike traditional evaluation methods that rely on follower counts or views, Glow.B calculates per-unit pricing based on internal revenue data and uses AI-powered crawling to analyze creators' advertising engagement frequency, recognizing that over 80% of creator income is generated through advertising. By combining these two indicators with other factors, Glow.B accurately evaluates the financial value of creators as a profession.
Glow.B’s innovative financial evaluation system expands access to financial services such as credit cards, loans, and investments, which were previously available only to top-tier creators. Now, Glow.B connects digital talent with financial opportunities, not only supporting individual creators but also fostering significant growth across the broader creator economy.
Optimizing Ad Revenue
Glow.B goes beyond simple data collection by analyzing transaction data between advertisers and creators to determine actual revenue. This process includes patented sentiment analysis of communication, which demonstrates an accuracy rate of 87.6%.
AI-based Income Estimates
Via Glow.B, advertising frequency is extracted from social media and combined with image recognition and time-series analysis to predict creators' revenue and growth trends with 90.27% accuracy.
Enhanced Financial Reports
Through hyperparameter optimization and cross-validation techniques, Glow.B significantly enhances the precision of its AI models, achieving 94.72% accuracy in distinguishing between ad and non-ad content. Additionally, the platform generates comprehensive financial reports within 30 seconds, which are then provided to traditional financial institutions via API.
PATENTS
SB23
Advertisement Provision System And
Method Using Customer Sensit by Big Data
A system and method for providing advertisements using customer sentiment analysis based on big data is presented. This system collects user data such as searches, payments, inquiries, and ratings, extracts relevant keywords, and uses big data to generate initial ad recommendations. It then refines these recommendations based on sentiment analysis from a database, further analyzing user sentiment to deliver final personalized ad recommendations to the user.
AR22
Non-face-to-face Authentication System for Fintech service Using AI-based Facial Recognition Algorithm and Method
A system and method for remote identity verification in fintech services using AI-based facial recognition algorithms is provided. The system includes a communication unit that receives verification data from the user device, a database to store the information, and a control unit to manage the verification process. The control unit generates random verification codes, hand gesture patterns, and facial recognition data for comparison with the user-provided inputs to complete the identity verification process.
