Projects using Python in SindhProjects using Python in Sindh๐ This the best I have done in health industry - A SaaS platform: https://treatmentnotes.com/
๐ Built an AI-powered behavioral health documentation platform designed for real clinical workflows. The system supports AI generated notes from live conversations, uploaded transcripts, and custom knowledge-base logic tailored to mental health and addiction treatment. It was designed for secure, scalable healthcare use with HIPAA ready architecture and EMR integration support.
๐ฏ Complete Tech Stack:
AI Summarization, Clinical Nuance Detection, FastAPI, Vite, React, AWS Bedrock, Anthropic Claude, PostgreSQL, pgvector, Vector Database, Retrieval-Augmented Generation (RAG), AI Agent Architecture, HIPAA Compliant Cloud, Speech-to-Text API, LLM Fine-tuning, Healthcare Interoperability, HL7/FHIR Integration, Serverless Backend, Semantic Search, Private LLM Deployment, Encryption at Rest, Python Backend Development.
๐ง What do you say Contra Community? Built a full-stack HRMS in under 2 weeks as a side project to dive deeper into Python and backend development!
Features so far:
Employee management with role-based access (Admin / HR / Employee)
Leave request workflow with approval/rejection
Attendance tracking โ clock in/out, monthly calendar view
Payroll engine โ tax brackets, overtime, pro-rated salary, PDF payslip download
Notifications, search, pagination, CSV exports
Dockerized and deployed
Stack: Next.js ยท TypeScript ยท Tailwind ยท FastAPI ยท PostgreSQL ยท SQLAlchemy
The backend was a new challenge for me: SQLAlchemy relationships, Alembic migrations, Decimal precision for payroll calculations, streaming PDF responses โ all of it was tricky at first, but Iโve learned a lot along the way.
URL: https://lnkd.in/dRg86PtQ
(https://lnkd.in/dRg86PtQ)This is just the beginning! I plan to add many more features. I designed and developed a complete AI Interview Intelligence Suite that brings 10 specialized AI agents together within a single platform.
Instead of building a single chatbot, I created a coordinated multi-agent system where each agent focuses on a specific stage of the interview journeyโfrom resume preparation and company research to technical practice, behavioral interviews, mock interviews, question prediction, and salary negotiation.
The platform includes AI Interview Coach Pro, Live Coding Interview, Behavioral Interview Trainer, Salary Negotiation Coach, Technical Question Bank, Resume Tailoring Tool, Mock Interview Assistant, Interview Cracker, Interview Question Predictor, and Company Research Assistant.
The system was developed primarily for educational and practical interview preparation, with a focus on creating specialized AI experiences rather than relying on one general-purpose assistant.
Tech Stack: Python, Node.js, RAG, AI/LLM APIs, and Multi-Agent Architecture. Lead Intelligence is a lead-generation engine that finds businesses worth pitching and tells you exactly why.
Finding good prospects usually means opening hundreds of websites by hand and guessing which ones are neglected. This tool does it automatically:
โข Scrapes local businesses from Google Maps
โข Visits every website with Playwright and detects 20+ technical faults
โข Identifies the site builder behind each site (9 builders recognised)
โข Scores each lead by sales potential, so the best prospects come first
โข Drafts personalised outreach based on the issues found on each site
โข Includes a Next.js dashboard to browse, filter and manage leads
By the numbers: 25 API routes ยท 22 Python files ยท 20+ site checks ยท 9 builders detected
Tech stack: FastAPI, Python, Playwright, Next.js 14, TypeScript, Tailwind CSS, SQLite
My role: Solo full-stack developer. I built the scraping pipeline, the audit engine, the lead scoring, the API and the dashboard.
#LeadGeneration #WebScraping #Automation #Python #FastAPI #Playwright #NextJS #TypeScript #TailwindCSS #SQLite #FullStackDevelopment #WebAudit #SalesAutomation #B2BLeads #GoogleMaps #OutreachAutomation #SaaS #Freelance #WebDevelopment #AITools AI-powered assistant using Google Gemini to automate inventory management, customer support, and order processing for online stores. Features chatbot support, real-time alerts, sales analytics, and product image analysis. Reduces manual work by 70%+ and handles customer inquiries automatically.
Key Features: AI chatbot, inventory alerts, order tracking, sales analytics, product image analysis, automated reporting, multi-language support
Tech Stack: Python, Flask/FastAPI, Google Gemini API, SQLite, HTML/CSS/JS
Target Users: E-commerce business owners, online store managers, dropshippers