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The final solution had to include a chat for all user types and a document library with the ability to share files.Ī social network visualized as a graph in the D3 library.The application should be able to recommend different social networks based on connection strength, the data you share in your forms and other attributes.Attributes of all entities in the database needed to be dynamic so that field values could be shared between different social networks.individual entities and field values needed to have different access rights). fields in a form) into various networks (i.e. All users should be able to share a part of their profile (i.e.

A quick and efficient search that would match users with companies and individuals based on their skills and social connections.

2 user types: companies and individuals (with the ability to add universities and other user types in the future).

All connections for each user had to be visualized as a graph using the D3.js library.

The app had a number of requirements that complicated its architecture and made it hard to choose an optimal tech stack: With social network analysis, investors would be able to assess startup teams based on quantitative methods.ĭifferent types of visualization available in the D3 library

They wanted to develop an app for the visualization of connections within and outside of startup teams. These are all essential questions but investors often have no quantitative ways to assess the team besides gut feeling.Īnd this is where our client’s idea comes into play. Is it well connected? What skills do they have? What networks do they have outside of the company? And one of the most important factors for any investor is the team composition. When searching for a startup that’s worth their money, venture funds have to consider dozens of parameters. There are many startups who need funding and there are lots of investors who are interested in the tech sector.īut bringing them together isn’t as simple as it sounds. They wanted to build a new type of social network to help investors find projects worth their time and money. Some time ago we were contacted by an early-stage startup. However, there might be a perfect database for such cases.Īs we learned during one of our recent projects, it is fast, flexible, and has a fantastic community.īut first, let’s take a look at our project and the requirements we were facing when choosing our tech stack. So it can be hard to pick an optimal tech stack. With networking applications, you can’t predict how many connections you’ll have in the future and how complex they’ll get. We often deal with projects that face a high level of uncertainty.