Hey DEV Community! 👋

I recently participated in a hackathon and built Samiksha AI, a universal review and comment analyzer designed to turn messy customer feedback into structured business intelligence.

🧠 The Problem

Generic star ratings on e-commerce platforms don't give business owners the full picture. Rule-based sentiment tools often fail to catch sarcasm, background noise (like shipping complaints), or aspect-specific product feedback.

🛠️ How I Built It

I developed a python-based architecture that leverages:

• Google AI Studio (Gemini API): For advanced parsing, noise filtering, and Aspect-Based Sentiment Analysis (ABSA).
• Streamlit Framework: To build an interactive, real-time executive report card dashboard.
• Plotly/Matplotlib: For rendering data distribution metrics dynamically.

📁 Repository & Code Architecture

The code is structured with a clean separation between the data backend, core analytical engine, and user interface. You can check out the full open-source implementation here:

👉 GitHub Repository: https://github.com/TechSakhi/Samiksha-AI

🔮 Future Roadmaps

Building this pipeline gave me a deep appreciation for computational linguistics and structured datasets. Next, I plan to leverage these foundational concepts to explore building an AI agent focused on language learning systems!

I would love to hear your thoughts, feedback, or suggestions on how to improve the architecture!