Inspiration
Many business owners and MSME executives struggle to effectively track their customers, leading to significant customer churn. Witnessing this challenge inspired us to create Bodhini, a platform that leverages the power of data science and machine learning to help businesses identify at-risk customers and implement measures to retain them, ensuring sustainable growth.
What it does
Bodhini is a comprehensive customer management platform that processes data provided by business and MSME owners in a structured format. This data is analyzed using advanced machine learning algorithms to identify vulnerable customers at risk of churn. The platform generates actionable insights and provides tailored recommendations to help businesses retain these customers or re-acquire those who have already churned. By transforming raw data into meaningful strategies, Bodhini empowers businesses to improve customer retention and acquisition.
How we built it
We developed Bodhini using the C# ASP.NET MVC architecture for the backend, ensuring a robust and scalable foundation. The platform is delivered as a React web application and a Flutter-based Android app for seamless accessibility. To enable efficient communication between the backend and the machine learning model, we built custom APIs and integrated them with MLflow for model management and deployment. This architecture ensures smooth data flow and real-time analysis, making Bodhini a reliable tool for businesses.
Challenges we ran into
One of the primary challenges we faced was deploying the machine learning model effectively. Initially, we encountered integration issues, but by leveraging MLflow, we successfully streamlined the deployment process, ensuring that the model performed seamlessly within the platform’s architecture.
What we learned
- The importance of seamless integration between machine learning models and production environments.
- Effective API design to ensure smooth communication between frontend, backend, and machine learning components.
- User-centric design principles for creating intuitive interfaces for business users.
- The value of iterative testing and feedback to refine the platform’s features.
What's next for Bodhini
Our immediate next step is to launch the Minimum Viable Product (MVP) at the hackathon and conduct extensive user testing. Based on the feedback gathered, we plan to implement rapid development cycles to enhance the platform’s features and usability. In the long term, we aim to expand Bodhini’s capabilities with additional analytics tools, integrations with popular business software, and support for more industries, ensuring it becomes an indispensable tool for customer management.
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