As most startups already know, being accepted into a business accelerator program can often mean the difference between the potential to succeed and the likelihood of failure.
Business accelerators basically work like this: a group of investors pool their collective resources to help fledgling companies grow into lucrative businesses. In exchange, these investors typically receive a percentage of the companies’ future equity. Ideally, this symbiotic relationship leads to financial gains on both sides.
However, Microsoft Accelerators are quite the anomaly because they do not demand an equity stake in the companies they mentor.
Always looking to expand its influence, Microsoft has business accelerators located in Bangalore, Beijing, Berlin, London, Paris, Tel Aviv, and Seattle. And just recently, the tech powerhouse announced that its Seattle Accelerator’s fourth run would specifically aid 10 later-stage companies involved in machine learning and data science:
- Cycle Computing
- DataRPM
- Datometry
- KenSci
- LoginRadius
- Metric Insights’
- Pymetrics
- Shareablee
- Tvision Insights
- Versium
According to Director of Microsoft Accelerator in Seattle Hanan Lavy, these lucky startups will collect $5.3M in average funding along with $3M in average annual recurring revenue. During the 4-month program, startup leaders will also work in collaboration with the Azure Machine Learning staff and Microsoft Sales reps to:
- Create product improvements
- Polish sales pitches
- Upgrade marketing tactics
- Find additional investors
- Enhance networking capabilities
- Utilize technological tools
- Facilitate customer involvement
But wait, there’s more. To further launch these startups into the big leagues, Accelerator Seattle will orchestrate an “Investor Demo Day” at the end of the program. The demo serves as an opportunity for startups to pitch their companies to an audience of angel investors, venture capital firms, industry leaders, and of course, Microsoft executives.
If these pitches attract funding, then who knows? These modest startups could one day become the biggest names in data science.