54th SICTIC Investor Day Zürich

Datum
04.09.2018 | 17:15 - 20:30
Veranstaltungsort
TI&M Zurich, Buckhauserstrasse 24, 8048 Zürich
Registrierung
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SICTIC invites startups interested in pithing to investors to submit their applications for the upcoming Investor Day.

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The SICTIC Investor Day is a match making event where tech startups pitch to find experienced investors and supporters. The event language is English. Questions from the audience are also taken in French and German (and translated if necessary).

This event is intended primarily for angel investors (also novices). Family offices, fund managers and venture capitalists that want to invest in Swiss Startups are also welcome to attend.

Startups selected to pitch include:

Orion Vault: building infrastructure for future of art investment & donations.

Signifikant.biz: revolutionize Mass Media Advertising: first, they automate campaign reporting. Second, they automate campaign planning. Third, they automate media buying.

eMonitor: a real estate B2B white-label CRM that digitizes and automates the rental process for apartment managers and sales process for home-vendors.

Starchain AG: a tech company focused on building the first universal platform, which enables premium manufacturers to protect, track, sell and promote their goods through a convenient digital end-to-end solution without interruptions.

Lucy Security AG: With the LUCY Phishing and Cyberprevention Sever they make simulated Internet Attacks an IT-Security Awarness Trainings available and affordable to everybody.

Travel Commerce Solutions AG: The different Airline Booking System - combining Flights and Ancillaries.

WeWent.com: aims to strengthen the human connection at workplaces by using technology. WeWent is based on an online marketplace for finding and booking the business-oriented team building activities, group training and workshops. The next step is turning it into an HR SaaS supported by team surveys and AI.

merakoi: Patient-enriched insights - they combine large-scale data collection and machine learning with patient expertise allowing them to systematically inject insights about the real life of patients into the drug development process.

 

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