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!
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