- Project TypeToken
- Platform Ethereum
- Circulating Supply120,198,713
- Total Supply1,226,667,278
- Max SupplyNone specified
- Primary SectorInfrastructure
- JurisdictionNone specified
Daniel Wischer is building great teams and products. Started as a developer for individual software development and managed software projects from small to large. Founded SquareMed company and built one of the largest diabetes management platforms for managing all diabetes related data. Since the development start of Magicline he is responsible for product management and built up the product management team from scratch to successfully roll out the new Magicline. Now conquering the world of sport and health as part of the executive team.
Kjeld Peters started his career as an intern during the dot-com bubble. Studied computer science afterwards and never left the internet industry. Worked in multiple software development teams as engineer and lead. Responsible for all aspects of operations and engineering. Manages teams (40+ engineers/developers) and runs platforms with millions of users and revenue. Provides executive leadership.
Jens Kappe studied computer science and economics and has more than 18 years of experience in building and operating large scale distributed web-apps and e-commerce platforms with two-digit million Euro-budget responsibility. Most valuable success so far was project leadership of agile transformation of methodologies, development and operations of otto.de. Cryptocurrency nerd since 2011 ;-) and spare time board game developer and owner of a small company.
Sven Eismann studied law when he realized that creating powerful campaigns, brands and networks kicks him even more. Being etat director at ddb hamburg for major clients like german Telekom and Siemens led to a deep understanding and a heart that beats for digital transformation in society ever since.
Questions and Answers
- 8 of 27 Team Members Verified
- Company Verified
- KYC Interview Conducted
Our proprietary TrustScore algorithm uses artificial intelligence machinery and combines dozens of data points including ID verification of every team member, company verification data, video interview with the project directors and dozens of additional data points offered by the projects such as social media profiles, white paper, questions and answers and many more to calculate the TrustScore.
A = Excellent
B = Good
C = Average
D = Below Average
E = Low