Online Registration of NetSol’s Incubator NSPIRE 2nd Incubation Cycle


NSPIRE, one of the largest business and tech incubators in Pakistan, has announced to accept the applications from the startups for NSPIRE 2nd Incubation Cycle. It is the best opportunity for those talented startups who want to prove themselves and do more.


The last date to apply is October 5, 2016, which will be followed by a proper recruitment process such as shortlisting, testing, screening and interviewing. Selection will be upon merit that will be determined considering the business ideas submitted by candidates and their commitments and potential of team members as well.

Netsol is doing well in Pakistani incubator section. It aimed to assist the creative and talented startups and entrepreneurs to launch their startups under its experienced mentors.

Both startup and teams are welcomed to share their ideas with NSPIRE and get the chance to turn the ideas into successful stories. If you are willing to submit the application then get ready yourself about the following information:




Target Market



Final Say/Commitment

There are no hard and fast rules. In team section, you have to describe your team and organization name if it exists. In the case of a startup, information regarding startup and idea will be required. Don’t hesitate to describe your idea/product/service and what it can do for the customers and society as a whole. What is the target market, its size, etc. is also the part of the form. And be prepared to tell about the finance required to meet the expenses and an overall summary of your idea.

It is much like a feasibility report so doesn’t forget to collect all areas before submitting the application. The more clear idea with a clear pathway and a committed team in case of team and startup in case of some person will bring the chance to get selected.

In order to apply online proceed here:

Jennifer Mccarthy

Jennifer is Associate Professor (Ph.D) at Air University. Research Interests: Informatics; analysis of large-scale biological data sets (genomics, gene expression, proteolytic, networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bio-informatics.

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