ProjectsAI / Machine Learning
Custora - AI Customer Intelligence Platform
An AI-powered customer intelligence dashboard that combines churn prediction, sentiment analysis, and LLM-driven recommendations to help businesses identify at-risk customers and make better retention decisions.
My Role
- 01Led the planning and overall development direction of the Custora AI customer intelligence platform.
- 02Designed the AI system architecture that connects customer data, machine learning models, LLM-based insight generation, and dashboard workflows.
- 03Planned the customer data retrieval flow from CSV upload, Supabase storage, ML inference, and AI-generated retention recommendations.
- 04Initiated the core idea of using AI to support customer retention decisions through churn prediction, sentiment analysis, and recommendation generation.
- 05Coordinated task distribution across frontend, machine learning, backend integration, and documentation.
- 06Built the visual dashboard UI using Next.js and connected the platform with Supabase as the main database.
- 07Prepared the ML model deployment flow using Azure ML and deployed the web application through Vercel.
- 08Advised and supervised ML model development for churn prediction and sentiment analysis.
- 09Assisted backend integration between the dashboard, REST API, ML model service, database, and LLM recommendation flow.
- 10Ensured the platform can transform raw customer data into churn risk insights, customer priority lists, and actionable retention decisions.
Features
- 01Secure dashboard access with login authentication.
- 02CSV Data Hub for uploading customer and review datasets.
- 03Customer churn prediction with churn probability and risk level classification.
- 04Sentiment analysis to understand customer feedback and review signals.
- 05Customer priority list to highlight users that need immediate retention action.
- 06Overview dashboard with KPI cards, charts, customer health summary, and trend visualization.
- 07AI recommendation panel that turns churn and sentiment results into retention action suggestions.
- 08REST API integration connecting the dashboard, database, ML model service, and LLM recommendation flow.
Impact
- Helps businesses detect at-risk customers earlier before they churn.
- Turns raw customer data and feedback into clear business insights.
- Supports data-driven retention decisions through churn risk, sentiment signals, and AI recommendations.
- Reduces manual analysis by combining prediction, visualization, and recommendation in one dashboard.
- Provides an end-to-end AI system, from data upload and ML inference to retention decision support.
Stack
Next.jsTypeScriptTailwind CSSSupabasePythonscikit-learnAzure MLVercel