Projects using Python in Pakistan

Projects using Python in PakistanProjects using Python in Pakistan

Cover image for Graph & Vector Database Architectire Development

Graph & Vector Database Architectire Development

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Cover image for From Fax to Brightree: Patient Intake for Healthcare Teams

From Fax to Brightree: Patient Intake for Healthcare Teams

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Cover image for TMBR | Portal

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Cover image for Sr.Python Dev | AI ML Engineer | Generative AI | Chatbots Expert

Sr.Python Dev | AI ML Engineer | Generative AI | Chatbots Expert

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Cover image for flower classification using deep learning

flower classification using deep learning

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Cover image for Receptionist AI – Intelligent Front Desk Automation

Receptionist AI – Intelligent Front Desk Automation

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Cover image for I helped streamline the lead-to-quotation

I helped streamline the lead-to-quotation process for a signage company. When a new lead comes in, we automatically use SerpAPI and RapidAPI to gather a list of potential vendors. Quotations are then requested from these vendors, submitted via email, and automatically extracted using Python. All leads, vendor info, and quotations are organized in Airtable, and the system intelligently selects the best quotation based on predefined criteria — all orchestrated seamlessly with Make.com (http://Make.com) automation.

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Cover image for LetsBuild

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Cover image for Revolutionary AI Agent for Automated 500K+ Award Updates

Built an autonomous AI agent that scrapes and updates 500K+ awards from across the web. The system intelligently finds new awards and refreshes existing data, reducing manual work by 80% and slashing update cycles from 6 months to just 3-4 weeks. Runs independently with minimal supervision.

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Cover image for Designed and built an AI-driven

Designed and built an AI-driven regulatory compliance assistant enabling financial teams to automatically analyze policies, draft compliant documentation, and evaluate regulatory risk in real-time. Key Achievements: Reduced manual policy review effort through automated AI-based document analysis. Built a RAG architecture combining scraped regulatory data and semantic retrieval. Implemented compliance scoring algorithms for structured risk evaluation. Integrated conversational AI for contextual regulatory Q&A.

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Cover image for “The voice you’re hearing is

“The voice you’re hearing is your own personalized AI assistant -- Homegirl.” Welcome to Momspreneur Match, a platform we recently launched to support mom entrepreneurs with clarity, structure, and execution. Momspreneur Match is built around a simple idea: Entrepreneurship should feel supported, not scattered.

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Cover image for AI-Powered Lead Generation & Automated

AI-Powered Lead Generation & Automated Email Workflow System This project is a fully automated lead processing and outreach system built using n8n, Google Sheets, and Gmail integration. The workflow is triggered by new entries in Google Sheets, processes data using custom JavaScript logic, categorizes leads by industry, and automatically sends personalized emails. After sending emails, the system updates lead status in separate sheets for tracking and reporting. Key Features: Google Sheets trigger for real time lead intake Custom JavaScript node for data processing & filtering Conditional routing based on industry categories Automated Gmail email sending Dynamic sheet updates for tracking responses Multi-branch automation architecture Technologies Used: n8n, Google Sheets API, Gmail API, JavaScript, Automation Logic

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Cover image for AuraExtract — Intelligent Invoice &

AuraExtract — Intelligent Invoice & Receipt Data Extractor The extraction engine uses intelligent regex pattern matching that handles real-world invoice layouts — column-per-line PDF formats, inline tabular formats, and plain text documents. It detects 10 fields automatically and parses up to 20 line items per invoice. Supports PDF, TXT, and DOCX formats. Includes a raw text preview panel so users can verify exactly what the engine is reading. CSV export includes both the summary fields and full line items table — ready to open directly in Excel. Pure Python. Zero external dependencies beyond pypdf for PDF reading.

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Cover image for ik-brohi/finger-tips-image-capturing-application-in-AI-machine-…

ik-brohi/finger-tips-image-capturing-application-in-AI-machine-…

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Cover image for I recently built an e-commerce platform for seamless online ...

I recently built an e-commerce platform for seamless online shopping and efficient product management, offering customers an intuitive experience to browse products, view details, compare prices, manage carts, and complete secure checkouts, while sellers can easily manage inventory, update listings, track orders, and monitor performance through a clean dashboard. The platform is designed with scalability and performance in mind, ensuring fast load times, responsive design, and reliable data handling across devices. Key Features: • Product browsing with detailed pages • Secure checkout and order management • Admin/seller dashboard for product and inventory control • Responsive, mobile-friendly UI • Modern and scalable architecture

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Cover image for Most AI assistants forget everything

Most AI assistants forget everything after a few messages, forcing users to repeat themselves and pay high API costs. My client faced this exact problem. I built a persistent AI memory platform that never forgets. Using ChromaDB for fast access and Qdrant for deep storage, it remembers every conversation, user preferences, and historical context across unlimited sessions — even after restarts. This system delivers near-perfect memory recall, instant context retrieval (<50ms), and up to 99% cost savings compared to traditional AI services. By intelligently injecting only relevant context, it saves hours of manual work and unnecessary compute. The platform is production-ready, Docker-deployable, and supports multi-model AI routing for efficiency and scale.

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