Sentique is a full‑stack feedback analytics platform that ingests user reviews from App Store, Google Play, Trustpilot, Reddit and Twitter/X, processes them with a fine‑tuned BERT model into 16 categories and sentiment labels, and provides comprehensive analytics and insights.

A Python major project developed during my Summer Industrial Training (2025).

A new package is designed to simplify the process of extracting structured information from user-provided text inputs by leveraging a language model with pattern matching capabilities. The system prom

An AI-based inventory optimization system that leverages machine learning to predict demand, recommend menu items, and streamline stock management for restaurants and food service businesses.. — all deployed through a real-time Stream lit web app.

📊 German Sentiment Analysis for Service Desk Feedback with TextBlob-de, Hugging Face's BERT, and Custom Self-Trained Models. Welcome to the German Sentiment Analysis project, where we utilize TextBlob-de, Hugging Face's BERT, and Custom Finetuned Models for analyzing customer feedback from a service desk.

AI-powered customer feedback analyzer — Gemini classifies sentiment (Positive/Negative/Neutral), logs to Google Sheets, sends email alerts via n8n

Feedback Recording System used by bank branches. The system is designed to record customer feedback regarding services provided at teller positions, provide reporting options, and include an administration module for managing branches, teller positions, and user roles.

A new package designed to take user input about accessibility challenges and generate structured summaries or actionable recommendations. It leverages advanced pattern matching with language model int

Develop a database to store and analyze customer feedback for a product or service.

A Rust crate for calculating Net Promoter Score (NPS) from survey responses.

Automated workflow using Make and Google Gemini to collect, analyze, and categorize customer feedback in real-time, reducing manual analysis time and enabling data-driven insights.

Automated workflow built in Zapier that analyzes customer feedback using GPT-4o Mini for sentiment classification, routing responses through personalized emails or escalation notifications via WhatsApp.

AI-driven platform for analyzing emotional tone and sentiment across social media platforms. This tool helps brands, organizations, and researchers understand public opinion, detect crises early, and make data-driven decisions.

n8n + Claude AI pipeline that clusters customer feedback from multiple sources into scored, prioritized themes - outputs to Markdown, Slack, or Notion

Turn raw customer feedback into actionable signals without human triage. This n8n workflow automation analyzes feedback using GPT-4.1, detects sentiment and intent, creates Jira issues when needed, and alerts teams in Slack. A flexible n8n workflow built for faster response and smarter product decisions.

Turn WooCommerce reviews into clear, actionable insights without manual reading. This n8n workflow automation analyzes customer reviews using GPT-4, stores structured feedback in Airtable and sends concise sentiment summaries to Slack — helping teams spot issues, trends and wins faster with a flexible n8n workflow template.

Analiza automáticamente el feedback de usuarios, reseñas o comentarios. Detecta idioma, clasifica el sentimiento, genera un resumen, identifica problemas comunes y sugiere recomendaciones para mejorar productos o servicios. Multilingüe y fácil de usar.

A production-style, multi-source feedback intelligence platform for product managers. Fetches live Google Play Store & App Store reviews, runs sentiment analysis, auto-detects bugs and feature requests, ranks issues by priority score, and generates stakeholder-ready weekly PDF reports — all via a real-time Streamlit dashboard.

turn player comments into a realistic dev to-do list.

Centralized platform for collecting, analyzing, and acting on user feedback