Freelancers using OpenAI in RawalpindiFreelancers using OpenAI in Rawalpindi
ProjectsPeople
Shehzada Ammad Ali's avatar
Shehzada Ammad Ali
Islamabad, Pakistan
Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert
1x
Hired
43
Followers
Full Stack Developer| n8n | Framer| Kajabee| Webflow Expert
Cover image for Human Resource Intelligence Chatbot with SQL-Driven Data Vis...
Human Resource Intelligence Chatbot with SQL-Driven Data Visualization I developed an AI-powered HR chatbot that transforms natural language queries into actionable insights through SQL-driven analytics and automated visualizations. How It Works: HR asks questions in plain English AI generates/executes SQL queries Processes workforce data Outputs structured results or charts Key Features: Natural language to SQL conversion Real-time workforce analytics Automated data visualization Scalable integration with HR databases Extendable to other chart types
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180
Cover image for Rat Paw Detection with YOLOv8 + Gradio This project showcase...
Rat Paw Detection with YOLOv8 + Gradio This project showcases a lightweight and intuitive web interface for detecting rat paws in images using a custom-trained YOLOv8 model. Built with Gradio, it allows users to upload an image and receive instant visual feedback with detected paws highlighted. Key Features: YOLOv8 object detection fine-tuned specifically for rat paw recognition. Interactive web app for image uploads and real-time inference. Built with Gradio for fast prototyping and deployment. Clean interface with automatic annotation overlay.
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190
Cover image for Contours Extraction & DXF Export from Images-AI-Based End-to...
Contours Extraction & DXF Export from Images-AI-Based End-to-end computer vision solution that automatically detects objects in an image, accurately measures in real-world units, &exports result as a scalable DXF file. Key Features Uses background subtraction & morphological operations, extract objects from image, even in cluttered or noisy backgrounds. Detects known reference object (coin) in image & computes precise scaling factor (mm/px) using OpenCV contours & geometric heuristics. Clean object edges are extracted & converted into vector contours with pixel-level precision. Object outlines are transformed into vector splines & exported as .dxf files, fully compatible with CAD tools like AutoCAD, LibreCAD, SolidWorks, & Fusion360. User-friendly frontend for non-technical users to upload images & receive DXF files .
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183
Cover image for AI Multlingual voice Chat Application Developed a Multilingu...
AI Multlingual voice Chat Application Developed a Multilingual AI Voice Chat App enabling real-time cross-language communication through AI transcription, translation, and voice cloning. Users exchange voice messages in their native tongues while preserving the sender's vocal identity. How it Works: Set preferred languages Send voice messages AI transcribes & translates Converts text to speech Clones sender's voice
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124
OpenAI(6)
Armughan Shahid's avatar
Armughan Shahid
proIslamabad, Pakistan
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
New to Contra
AI SaaS Dev | LLMs, Agents, Voice & Automation | Web, Mobile
Cover image for InForm - AI-Driven Physiotherapy App
InForm - AI-Driven Physiotherapy App for Diagnosis, Rehab & Recovery Tracking The core problem it solves: Patients struggle to get timely, structured physiotherapy guidance, while physiotherapists are overwhelmed managing cases, tracking progress, and creating personalized rehab plans manually. Existing systems either lack intelligence or lack control. This product creates a complete digital workflow where diagnosis, communication, and recovery are all connected into a single system. What was built: A full AI-powered physiotherapy platform with mobile apps for patients and a web-based admin system for physiotherapists. Patients begin by submitting structured symptom data through guided questionnaires. Instead of jumping directly to conclusions, the system uses an AI diagnosis engine to analyze patterns and generate internal clinical suggestions. These suggestions are never shown to patients, they act as decision support for physiotherapists, ensuring every diagnosis remains human-approved. Once a case is created, physiotherapists review patient data, validate or override AI recommendations, and communicate directly through an in-app messaging system. Every interaction is tied to a structured case, ensuring context is never lost. The system then moves into recovery management. Physiotherapists create personalized rehab plans with multi-phase programs, exercise libraries, and video guidance. Patients follow these plans inside the app, logging progress, completing KPI-based milestones, and moving through recovery phases in a structured way. A key part of the system is the progress tracking engine. Patients log metrics, complete phase-based goals, and unlock new stages only when criteria are met. Physiotherapists get real-time visibility into adherence, performance, and patient feedback, making the system both trackable and measurable. Alongside this, an intelligent chatbot handles general queries and reduces load on physiotherapists. When confidence is low or cases become complex, the system escalates conversations into structured cases with full context preserved. Technical architecture: Built as a scalable mobile-first system using React Native for patient apps and React.js for the admin panel, with a Node.js/Nest.js backend and Python powering AI-driven diagnosis logic. Data is managed through PostgreSQL, with secure authentication and encrypted communication layers. The AI layer is designed as a support system, not a replacement. It uses LLM-based reasoning to assist diagnosis and continuously improves through feedback loops based on physiotherapist decisions, creating a human-in-the-loop learning system. Deployed on cloud infrastructure (AWS/GCP), with Stripe integration for subscription-based access and a modular architecture designed for future AI expansion. Business model built in from day one: Subscription-based access for patients, with clear pathways to expand into AI-assisted rehab recommendations, outcome analytics, and protocol optimization. The system is designed to evolve into a data-driven recovery platform where every patient interaction improves future treatment accuracy, turning clinical workflows into scalable intelligence.
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104
Cover image for AI Operations Agent: RAG-Powered Retail
AI Operations Agent: RAG-Powered Retail Intelligence & Task Automation This project was built for large-scale restaurant groups and multi-unit retail operators who manage high volumes of data across dozens or hundreds of locations. Specifically designed for Regional Managers and Operations Directors, the system serves as an enterprise-grade "Digital Consultant" that bridges the gap between fragmented POS/inventory data and daily on-the-ground execution. By transforming millions of rows of restaurant performance metrics into high-priority tasks, it provides a centralized platform for leadership to monitor KPIs, approve AI-suggested corrective actions, and ensure operational consistency across their entire portfolio. 1. What We Built We developed a production-ready Autonomous AI Operations Agent designed to bridge the gap between complex retail data analysis and daily execution. The system acts as a digital consultant for regional managers, transforming raw KPIs into actionable tasks. Analytical AI Chat: A free-form conversational interface where users can query performance data (e.g., "Show me the top 5 worst profitable stores in Istanbul for the last 3 months"). Task Management Dashboard: A structured workflow where AI-suggested actions are automatically logged for manager approval or rejection. Automated Action Logic: The agent uses an "Action Suggestion Map" to identify specific defects (like low audit scores or high food waste) and suggest precise corrective measures. Persistent Memory: Includes both short-term memory for the current chat session and long-term RAG memory to maintain context over time. 2. How We Built It (The Stack) The system was engineered for scalability and reliability using a modern, containerized stack:AI Orchestration: LangGraph was used to manage complex, multi-turn reasoning and agentic workflows. Frontend: React/Next.js 14 for a responsive, real-time user interface. Backend & Data: Node.js paired with a PostgreSQL database capable of handling 1M+ records. LLM Access: Integrated via OpenRouter to allow for flexible model selection and switching. Infrastructure: Fully Dockerized to ensure consistent deployment across environments. 3. Challenges We Faced As the system scaled from prototype to processing millions of records, we encountered several critical engineering hurdles: Response Latency: The initial monolithic prompt architecture led to response times exceeding 60 seconds, far slower than the required "ChatGPT-like" speed. Prompt Verbosity & Errors: Complex questions involving multiple variables caused the LLM to lose focus, leading to "reasoning errors" and incorrect SQL generation. Hallucination Risks: In multi-branch queries, the model occasionally fabricated data points, particularly around manager hours and performance metrics. Context Switching Bugs: The agent sometimes struggled to "let go" of a previous topic, continuing to reference an old store when the user had asked about a new city. 4. How We Solved It We re-engineered the core pipeline to transition from a single, heavy agent into a Modular Multi-Step Architecture: 75% Latency Reduction: By decomposing the main logic into smaller, task-specific nodes, we dropped processing time from 60s down to 15s. Task Decomposition & Specialized Models: We stopped using a "one-size-fits-all" model. Instead, we implemented a router that uses lighter, specialized models for SQL generation and action identification, and flagship models only for final reasoning. Granular SQL Generation: Breaking the metadata analysis into narrow sub-steps eliminated SQL hallucinations. The model now only "sees" the specific schema needed for the current sub-task, ensuring 100% accuracy. 10-Point Testing Protocol: We implemented a rigorous QA protocol that specifically verified bug fixes for context switching, task duplication, and chart coverage before final delivery.
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120
Cover image for BudgetNest — AI-Powered Personal Finance
BudgetNest — AI-Powered Personal Finance SaaS Most people don't track their finances because the friction is too high. BudgetNest removes that friction entirely, every transaction captured automatically, categorised intelligently, and surfaced through analytics that actually help people make better decisions. The core problem it solves: Manual expense logging fails because people forget, get lazy, or simply don't have time. BudgetNest built an automated capture layer that works across every channel a user already operates in i.e. SMS alerts, bank emails, receipt photos, WhatsApp messages, and voice notes in English and Urdu. The system deduplicates intelligently across all input sources so nothing gets logged twice regardless of how it came in. What was built: A complete AI finance platform with five distinct automated capture modes SMS and email parsing for bank transaction alerts, PDF and image bank statement upload with AI extraction, OCR receipt scanning via camera, a WhatsApp bot that accepts text, images, and voice notes, and multilingual voice input for manual cash payments. Every transaction flows through an LLM-powered categorisation engine that auto-assigns categories and subcategories, recognises vendors, and learns from behaviour over time. Beyond capture, the system includes smart budgeting with AI-driven suggestions based on spending patterns, subscription detection for recurring transactions, shared expense and split-bill tracking, fraud detection for unusual transactions, and forecasting that projects deficit against income. Dashboards surface everything through charts, trend lines, and weekly and monthly summaries. Technical architecture: React Native across iOS and Android, Node.js and FastAPI backend, PostgreSQL and MongoDB, AWS infrastructure with EC2, S3, and RDS, Python-based NLP and OCR pipeline using Transformers and Tesseract, Twilio WhatsApp integration, Gmail API for email parsing, and Firebase for push notifications. Business model built in from day one: Freemium with premium automation features, B2B white-label capability for microfinance institutions and NGOs, and the OCR and SMS parsing logic architected as standalone APIs for third-party licensing meaning the AI layer has revenue potential independent of the consumer app.
1
143
Cover image for We Step Together - Step-to-Donation Mobile App
We Step Together - Step-to-Donation Mobile App
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2
OpenAI(3)
Waqas Shah's avatar
Waqas Shah
Rawalpindi, Pakistan
Webflow, Bubble, Retool Developer | Ai Automation Specialist
$1k+
Earned
1x
Hired
5.0
Rating
11
Followers
Webflow, Bubble, Retool Developer | Ai Automation Specialist
Cover image for Built an AI-Powered Content Creation System: What Should I A...
Built an AI-Powered Content Creation System: What Should I Automate Next? Just finished building a complete AI content creation workflow in n8n, powered by OpenAI and Google Sheets. Here’s what it does 👇 🧩 Pulls content ideas from Google Sheets 🔍 Gathers real-time research via Tavily ✍️ Uses OpenAI to write blog + LinkedIn + Facebook posts 📤 Sends everything back into Google Sheets, ready to post What used to take hours now happens in under 2 minutes, fully automated, no code needed. Now I’m curious... 💭 If you could automate one part of your business or workflow, what would it be? I’m looking for my next automation project, and I’d love to build something inspired by your ideas. Drop your automation ideas below, let’s see what we can create next ⚙️✨
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129
Cover image for Complete website redesign & Webflow Implementation
Complete website redesign & Webflow Implementation
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1
Cover image for LunVoya Travel Platform Development
LunVoya Travel Platform Development
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3
Cover image for Multiversx - WebFlow
Multiversx - WebFlow
0
12
OpenAI(1)
Evox AI Tech's avatar
Evox AI Tech
Islamabad, Pakistan
AI Chatbots · Calling Agents · Websites for Restaurants 🤖.
New to Contra
AI Chatbots · Calling Agents · Websites for Restaurants 🤖.
Cover image for AI Chatbot for Restaurant —
AI Chatbot for Restaurant — Automated bookings, menu queries & customer support in Arabic & English. Built with Voiceflow & OpenAI.
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31
Cover image for Most restaurant owners don't realize
Most restaurant owners don't realize this: Their website is open 24/7. But their customer support isn't. 😕 That's exactly what we fixed for our client. We built an AI Chatbot for a restaurant that: ✅ Answers menu questions instantly ✅ Takes reservations automatically ✅ Handles complaints without human help ✅ Works in Arabic & English both Result? 📞 Zero missed inquiries ⏰ Staff saved 3+ hours daily 💰 30% more table bookings in first month This is what we do at EVOX AI TECH. AI Chatbots + WordPress Websites specifically built for restaurants. Want the same for your restaurant? 👇 Message me — let's talk.
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3
152
Cover image for WordPress Website for Restaurant — SEO Optimized
WordPress Website for Restaurant — SEO Optimized
1
0
Cover image for AI Chatbot Development for Restaurant — 24/7 Automated Support
AI Chatbot Development for Restaurant — 24/7 Automated Support
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2
OpenAI(2)
Ghulam Mohiuddin's avatar
Ghulam Mohiuddin
Islamabad, Pakistan
Swiftly coding your iOS dreams to reality
Swiftly coding your iOS dreams to reality
Cover image for Back in 2021 when I
Back in 2021 when I started my career as an iOS Developer, this was my first project that I worked on. This is an app where users can connect with friends, create events and invite others etc. I started as a junior developer fixing smaller bugs, then I learnt and refined my skills and became a senior developer. I coordinated with the team on estimating, planning, implementing new features. I along with other team members, redesigned this app, implemented numerous features, fixed memory leaks, implemented AI, stripe payments. It was initially built in UIKit, but while redesigning we chose SwiftUI. Screen by screen in each sprint we completely made it into a SwiftUI app, which reduced the development times by a lot. I learnt a lot while working on this project, actually I learnt both Swift and SwiftUI while working on it.
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63
Cover image for This was my first big
This was my first big project as a Freelancer. I built a fully-featured smart reminder app enabling users to create tasks manually or through AI-powered commands. I integrated In-App Purchases, added WidgetKit support, SiriKit voice commands, Action Button shortcuts, and implemented a Timeline interface with animations. I also built the backend and implemented OpenAI-driven natural language task creation. Implemented localisation to support both Hungarian and English language in app. The project focused heavily on use experience, speed, and reliability.
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50
Cover image for This was my second big
This was my second big project as Freelancer. Invoza is a comprehensive invoicing app built for freelancers and small businesses. I designed and developed the entire iOS app using SwiftUI, implementing features such as invoice and estimate creation, PDF generation and export, multi-currency support, client management, and customisable invoice templates. The app features a clean, intuitive interface that makes billing effortless, with support for recurring invoices, payment tracking, and detailed financial reports. Built with a focus on user experience, reliability, and professional presentation.
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Cover image for SlyAI is an entertaining AI-powered
SlyAI is an entertaining AI-powered app designed for creating hilarious prank images and videos. I developed the complete iOS application using SwiftUI, integrating advanced AI image and video generation APIs. The app allows users to easily create convincing prank content with intuitive controls and fast generation times. Built with a focus on fun user experience and seamless content creation workflows.
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16
OpenAI(1)
Zahoor Ahmad 's avatar
Zahoor Ahmad
Rawalpindi, Pakistan
n8n Automation Engineer | Workflow & API Integrations
New to Contra
n8n Automation Engineer | Workflow & API Integrations
Cover image for AI E-commerce Customer Support Automation
AI E-commerce Customer Support Automation
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2
Cover image for AI business Assistant automation
AI business Assistant automation
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2
Cover image for Multi-Platform Video Auto-Poster with Smart
Multi-Platform Video Auto-Poster with Smart Hashtags🚀
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43
Cover image for 🚀 AI Agency — Lead
🚀 AI Agency — Lead Automation v2.1 (Audited & Fixed)
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33
OpenAI(1)