Online Platform to Connect Investors with Startups

The client approached Capital Numbers to create the above web application from scratch. He wanted a matchmaking platform for startups and investors. His objective was to bring together startups, business angels, venture capitalists, corporates, etc., on one page. So, he wanted to create a web app where endless collaborations could occur. And therefore, he contacted Capital Numbers to help him make the web app.

But, the client’s briefs were vague when he came to us. So, Capital Numbers offered the client help in clarifying his ideas.

For example, we asked the client open-ended questions to understand what he wanted from us. We asked him questions tailored to his end goals and budgets so that we get facts on paper and don’t end up underperforming or overperforming. We asked him about his scalability needs and target groups.

We picked up clues from his inputs and formulated a roadmap. In creating the roadmap, we found we had to address challenges around the following areas:

• Multi-user dashboards
• Dynamic web pages
• Advanced searches
• Granular filtration
• Quick page reloads
• SERP ranks
• App speed

We jotted down these points and aimed to focus on them. We took job portal development as our reference. For example, job portals have custom codes that help match candidates with employers. Similarly, this app involved the integration of custom codes in matching startups with investors. So, we started our work accordingly.

We began our work with the background literature we had in hand. Our team included one backend developer and two frontend developers. Unlike many engagements that rely on predefined contracts, this one didn’t have preset milestones. So, we took an Agile development approach to implement and iterate solutions as we went along.

Our solutions included the following:

Firstly, we set up the backend using Python. Python comes with an extensive set of libraries well-suited for creating rich ecosystems. It comes with embedded forms that capture thousands of user data and inputs. Its object-oriented design adds to app performance, too.

We also used Docker to convert the backend structure into individual containers. Each Docker container is easy to test and deploy. Therefore, we divided the structure into Docker containers to make the app more maintainable.

For the frontend, we used ReactJS. We chose ReactJS because it allows code flexibility and reusability. Its modularity helps developers adjust different UI components. We also used Redux to manage the state in React and ensure the React components behave as expected. In addition, we used Tailwind CSS to display user profiles in a visually engaging way.

For the database, we chose MongoDB. The best part about using MongoDB is that it helps query deep into documents and perform complex data analysis with just a few codes. So, MongoDB was our instant choice for storing, securing, and querying user data.

We wrote several if/then logic to define the user flow and match investors with startups. We tested every logic, UI element, and conditional statement before we deployed the final product on AWS.

We chose AWS because it’s perfect for computing data-heavy apps. It helps process thousands of data without fail - precisely what we needed.

We implemented the solutions and rolled out the product in just 9 months. Because we had in-depth Python programming skills, we could build this complex ecosystem within this time. The final product is a beautiful ecosystem where startups and investors meet. Here’s what resulted because of our work: