Freelancers using FastAPI in PunjabFreelancers using FastAPI in Punjab
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Muhammad Talha's avatar
Muhammad Talha
Lahore, Pakistan
Full Stack Developer | AI & Automation
9
Followers
Full Stack Developer | AI & Automation
Cover image for Kaizen is a Python learning
Kaizen is a Python learning platform for kids ages 12-14 — that specific age window matters because most coding-for-kids products target either much younger (Scratch/blocks) or much older (Codecademy-style courses for adults). The 12-14 zone is underserved: they've outgrown drag-and-drop blocks but they're not ready for "Watch this 2-hour video and take notes." The product is built around a narrative: the digital realm of Coderia is being corrupted, and the kid's job is to save it by writing real Python. Eight story realms (Echo Valley → Logic Peaks → Loop Lakes → ...), 94 lessons, one connected arc. Every lesson is real Python that runs, not blocks.
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Cover image for High-Performance RAG Application Development
High-Performance RAG Application Development
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Cover image for AI News Automation Bot
AI News Automation Bot
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Cover image for I designed and built a
I designed and built a full-stack AI healthcare platform from the ground up integrating 6 external medical APIs, real-time AI-powered consultations and a production-grade frontend with smooth animations. This is the kind of intelligent and scalable system I can build for you in healthcare, education or any data-driven domain. Live Demo: healix.vercel.app (http://healix.vercel.app) What Healix Does 4.6 billion people worldwide lack access to essential health services. Healix bridges that gap by putting an AI health companion in every citizen's pocket backed by trusted data from WHO, NIH and the FDA. It delivers 24/7 health guidance, reduces unnecessary ER visits and extends the reach of overstretched healthcare systems. Core Features I Built AI Health Chat - 24/7 intelligent consultations with multi-language support powered by Google Gemini Symptom Checker - Interactive symptom analysis with triage recommendations using NIH Clinical Tables Drug Interaction Checker - Cross-checks multiple medications for dangerous interactions via OpenFDA Medicine Search - Detailed drug profiles including side effects and usage guidelines from OpenFDA and RxNorm Health Dashboard - Personalized health overview with activity tracking and chronic disease management Additional modules include mental wellness tracking, nutrition logging, lab results management, vaccination records, appointment booking and a community health forum. Tech Stack Next.js 15 and React 19 frontend styled with TailwindCSS and animated with Framer Motion. Python FastAPI backend powered by Google Gemini AI with fallback handling. Integrated with OpenFDA, NIH Clinical Tables, PubMed, RxNorm and WHO data sources. Supabase authentication with Google OAuth. SQLite for development and PostgreSQL for production. Deployed on Vercel. What This Demonstrates Complex multi-API orchestration with error handling and fallback logic AI integration with prompt engineering for accurate medical responses Clean component architecture with 30+ routes and reusable UI components Full authentication flow with role-based access Responsive design optimized for mobile-first healthcare access Production deployment with real users in mind Looking to build an AI-powered platform for your industry? Whether it's healthcare, education, finance or operations I can architect and ship intelligent systems like this end to end. Let's talk.
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FastAPI(3)
Arslan Mehmood's avatar
Arslan Mehmood
Lahore, Pakistan
ML AI | Backend | Computer Vision | GenAI | LLM Agents
New to Contra
ML AI | Backend | Computer Vision | GenAI | LLM Agents
Cover image for Shelfr - AI-Powered Retail Shelf
Shelfr - AI-Powered Retail Shelf Intelligence Platform I led the development of Shelfr as the Senior Computer Vision Engineer and Lead Developer, taking the platform from the initial idea and system architecture through development, deployment, and production operations. My work included: 🔹 Designing the complete computer vision and backend architecture 🔹 Building product detection, shelf analysis, OCR, and image-processing pipelines 🔹 Developing APIs and scalable data-processing workflows 🔹 Deploying and managing production systems on GCP cloud servers 🔹 Optimizing model accuracy, processing speed, and infrastructure performance 🔹 Managing production monitoring, reliability, troubleshooting, and ongoing improvements 🔹 Leading technical decisions across AI, backend, cloud infrastructure, and DevOps The platform converts real-world retail shelf images into structured product and shelf-level insights, helping automate retail auditing, product visibility analysis, and inventory workflows. #ComputerVision #RetailAI #LeadDeveloper #AIEngineering #GCP #MLOps #Python #CloudEngineering
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Cover image for ⚖️ Built a French Legal
⚖️ Built a French Legal AI Assistant powered by advanced RAG and LLM technology. The system enables users to ask complex legal questions and receive accurate, context-aware answers grounded in French legal documents. Key features include: 🔹 Custom legal document ingestion and chunking 🔹 Metadata-based vector search 🔹 Hybrid retrieval and reranking 🔹 Agentic RAG workflows using LangGraph 🔹 Source-grounded answers with legal references 🔹 Private deployment on an Azure VM using locally hosted LLMs The main focus was improving retrieval accuracy, reducing hallucinations, and making large collections of legal documents easier to search and understand. #LegalAI #RAG #LLM #ArtificialIntelligence #LangGraph #Azure #GenerativeAI #MachineLearning
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Cover image for AI Vision for Retail, Industrial
AI Vision for Retail, Industrial & Monitoring Workflows Overview I have built and deployed multiple real-world computer vision systems for industrial inspection, retail automation, and monitoring workflows. My responsibilities covered: 🔹 Dataset preparation and labeling 🔹 Object detection model training 🔹 Segmentation model training 🔹 YOLO-based detection and tracking 🔹 Image/video inference pipeline development 🔹 Model evaluation and threshold tuning 🔹 Production deployment support 🔹 Cloud server management and optimization 🔹 Building practical AI workflows for real-world operational environments Fish Quality Inspection System - lythium.cl (http://lythium.cl) I led the development of an advanced fish quality inspection solution for an industrial workflow. The system used image analysis to monitor fish quality and support automated fish sorting based on AI predictions. 🔹 Led the development of an advanced AI-powered fish quality inspection system for an industrial workflow. 🔹 Built an image analysis pipeline to monitor fish quality from production-line images. 🔹 Trained object detection models to identify fish and relevant visual quality indicators. 🔹 Trained segmentation models to support more detailed visual inspection of fish regions. 🔹 Designed the AI workflow to support automated fish sorting based on model predictions. 🔹 Worked on inspection logic that could classify or route fish based on quality-related outputs. 🔹 Designed the system for conveyor-belt usage, where images need to be processed consistently and reliably. 🔹 Focused on production issues such as image quality, camera consistency, lighting variation, and model reliability. 🔹 Helped convert visual inspection from a manual/rule-based workflow into an AI-supported inspection pipeline. 🔹 Built the system to reduce manual inspection effort and improve production workflow efficiency. Shelfr.ai (http://Shelfr.ai) - Retail Automation Platform I developed AI image solutions for retail automation and execution. The system handled large-scale product detection across 10,575+ SKUs, price tag detection, shelf and display type detection, and gap detection for empty shelf spaces. 🔹 Developed large-scale AI image solutions for retail automation and execution. 🔹 Worked on product detection across 10,575+ SKUs, where each SKU represented a unique product. 🔹 Built object detection workflows to identify products from retail shelf images. 🔹 Developed price tag detection to locate and extract price label areas from store images. 🔹 Worked on shelf and display type detection to understand the retail environment layout. 🔹 Built gap detection logic to identify empty shelf spaces and out-of-stock areas. 🔹 Supported computer vision workflows for retail compliance, shelf monitoring, and store execution. 🔹 Worked with high-volume image data and production-level inference requirements. 🔹 Managed high-load production servers on Google Cloud Platform. 🔹 Implemented load balancing and autoscaling to improve system stability under production traffic. 🔹 Focused on scalable AI infrastructure capable of handling real-world retail image workloads. 🔹 Helped create AI systems for inventory visibility, shelf condition monitoring, and retail execution analytics. lake-shield.com (http://lake-shield.com) - USA LAKES - Boat Detection & Inspection System 🔹 Worked on a YOLO-based boat detection, tracking, and monitoring system. 🔹 Labeled datasets for boat detection and inspection model training. 🔹 Prepared image/video data for object detection training workflows. 🔹 Trained YOLO object detection models to detect boats in monitoring footage. 🔹 Built a detection pipeline capable of identifying boats from visual data. 🔹 Worked on boat tracking logic to monitor boat movement across frames. 🔹 Supported inspection and monitoring workflows using computer vision predictions. 🔹 Developed an end-to-end pipeline from labeled data to trained model and inference output. 🔹 Focused on practical model performance in outdoor environments where lighting, distance, angle, and background can vary. 🔹 Helped build a monitoring system that could support automated detection and review instead of fully manual observation. My Responsibilities Across These Projects 🔹 Led AI/computer vision system development 🔹 Designed labeling and dataset preparation workflows 🔹 Trained YOLO/object detection models 🔹 Trained segmentation models where needed 🔹 Built image and video inference pipelines 🔹 Evaluated models using practical production metrics 🔹 Improved model performance through dataset cleanup, retraining, and threshold tuning 🔹 Integrated AI models into backend or operational workflows 🔹 Supported production deployment and infrastructure optimization 🔹 Worked with real-world constraints such as lighting, camera angle, image quality, latency, and false detection rates Technologies Used 🔹 Python 🔹 YOLO / YOLOv8 🔹 Object Detection 🔹 Image Segmentation 🔹 OpenCV 🔹 PyTorch 🔹 FastAPI 🔹 Google Cloud Platform 🔹 Linux Servers 🔹 Load Balancing 🔹 Autoscaling 🔹 Custom Data Labeling Workflows 🔹 Model Training 🔹 Model Evaluation 🔹 Inference Pipeline Development 🔹 Production AI Deployment
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Cover image for LakeShield - AI-Powered Video Monitoring
LakeShield - AI-Powered Video Monitoring and Vessel Intelligence Platform I led the development of LakeShield as the Senior AI/ML Engineer and Lead Developer, taking the platform from initial research and experimentation to a scalable production system. My responsibilities included: 🔹 Designing the end-to-end AI and video-processing architecture 🔹 Building YOLO-based boat and vehicle detection pipelines 🔹 Developing object tracking and movement-analysis workflows 🔹 Implementing OCR for extracting boat registration information 🔹 Creating scalable pipelines for processing thousands of surveillance videos 🔹 Developing FastAPI backend services and automated data workflows 🔹 Building a Next.js analytics dashboard integrated with Supabase 🔹 Deploying and operating the AI pipeline on cloud GPU infrastructure 🔹 Optimizing model accuracy, inference speed, infrastructure costs, and reliability 🔹 Managing production monitoring, troubleshooting, maintenance, and continuous improvements The platform transforms raw surveillance footage into structured operational insights, enabling automated vessel monitoring, vehicle activity analysis, registration extraction, and reporting. This project involved complete technical ownership across Computer Vision, AI/ML, backend development, cloud infrastructure, data engineering, MLOps, and production operations. #ComputerVision #VideoAnalytics #ArtificialIntelligence #ObjectDetection #OCR #MLOps #FastAPI #NextJS #Supabase #CloudEngineering
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FastAPI(3)
Haris M.'s avatar
Haris M.
proLahore, Pakistan
Full Stack Web & Mobile Dev | Next Js | AI Agent | React
1x
Hired
5.0
Rating
26
Followers
Full Stack Web & Mobile Dev | Next Js | AI Agent | React
Cover image for Fancraft: Your AI-Powered App Review Management Platform
Fancraft: Your AI-Powered App Review Management Platform
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Cover image for Northward Capital Investment Platform Development
Northward Capital Investment Platform Development
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Cover image for Chat Buddy – Real-Time Mobile Chat Application Development
Chat Buddy – Real-Time Mobile Chat Application Development
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Cover image for Prodigi Studios
Prodigi Studios
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6
FastAPI(1)
Ali Hassan's avatar
Ali Hassan
Lahore, Pakistan
Sr.Full Stack Consultant and Developer with 8+ years of exp
$10k+
Earned
1x
Hired
5.0
Rating
12
Followers
Sr.Full Stack Consultant and Developer with 8+ years of exp
Cover image for AI-Powered Voice Consultation Platform for Remote Healthcare
AI-Powered Voice Consultation Platform for Remote Healthcare
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Cover image for Exploring structured prompting with Kittl. For
Exploring structured prompting with Kittl. For this entry, I created a cinematic luxury footwear concept that captures the moment just before completion, where each component comes together to form the final design. The project includes a women’s high heel video and a three-image sneaker composition, focusing on detail, craftsmanship, and premium aesthetics through realistic textures and refined branding. This highlights how structured prompting can transform an idea into a visually polished result.
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Cover image for 🔥 Full-Stack Development - RankBee
🔥 Full-Stack Development - RankBee AI I worked as a Full-Stack Developer on RankBee an AI visibility platform that helps brands track and improve how they appear across AI search engines. 💡 Key contributions: ⚡ Interactive dashboards for AI visibility ⚡ Tools to track competitors and benchmark presence ⚡ AI-driven content optimization workflows ⚡ Prompt-based testing systems ⚡ Streamlined data processing into actionable insights The platform shows how AI interprets a brand which competitors are recommended and how to optimize content for better AI visibility. I focus on solving complex technical challenges and delivering products that give businesses a real advantage. If you’re developing AI-driven tools or ambitious platforms, let’s collaborate.
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Cover image for I also designed and developed
I also designed and developed https://infinite-compute.com/, a cloud-powered platform that enables users to access high-performance GPU machines and run demanding 3D tools directly from the web without expensive local hardware. I built the complete system architecture myself including the frontend backend services and cloud infrastructure focusing on performance reliability and secure access to remote computing resources. The platform provides a responsive interface to launch and manage GPU sessions while the backend handles session orchestration user management and compute allocation. The system was designed to maintain stable remote sessions efficiently manage resources and provide secure authentication so developers designers and 3D artists can run heavy software on demand from anywhere.
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FastAPI(1)
Muhammad Ahmad Mansoor's avatar
Muhammad Ahmad Mansoor
Lahore, Pakistan
Engineering intelligent solutions with AI.
5.0
Rating
2
Followers
Engineering intelligent solutions with AI.
Cover image for 🚀 Built an AI Receptionist
🚀 Built an AI Receptionist for Healthcare — Here's What It Can Do Managing a healthcare front desk is challenging. Calls, appointment scheduling, patient questions, and administrative tasks often overwhelm staff, leading to long wait times and missed opportunities to deliver a great patient experience. To address this, I built an AI Receptionist MVP designed specifically for healthcare providers. It can answer calls, schedule appointments, manage inbound and outbound communication, and respond to patient inquiries—all while staying within appropriate clinical boundaries. Here's what it demonstrated during a live test with our demo clinic, Evergreen Community Health Center: 🧠 Intelligent Patient Conversations Rather than following a fixed script, the AI understands context and knows its limitations. ✅ Recognized that dermatology wasn't offered and suggested available services instead: General Practice Pediatrics Physical Therapy Dental Care ✅ Clearly avoided giving medical advice by responding: "As a receptionist, I'm not qualified to provide medical advice." ✅ Offered the appropriate next steps by either: Booking a GP appointment for an initial assessment, or Transferring the caller to clinical staff for medical questions. 📅 Smart Appointment Scheduling The AI schedules appointments based on both clinic policies and patient preferences. During the demo, it: Collected the patient's information. Suggested the next available appointment. Adjusted the booking when the patient requested a later time. Checked clinic operating hours automatically and successfully booked a 5:00 PM appointment before closing. 💳 Administrative Automation Beyond booking appointments, the AI also handled routine administrative tasks by: Explaining consultation fees. Answering policy-related questions. Confirming referral procedures. Collecting the patient's email for appointment confirmation. ⚡ Built for Scale Unlike a traditional reception desk, the AI can handle thousands of conversations simultaneously. That means: No busy signals No waiting queues No missed calls Better patient accessibility 24/7 ⚙️ Easily Customizable Every healthcare provider operates differently. The AI can be configured with: Clinic-specific services Staff availability Business hours Appointment rules FAQs Internal workflows making it adaptable to virtually any healthcare organization. This project demonstrates how conversational AI can streamline healthcare operations while allowing staff to spend more time focusing on patient care. I'm excited to continue expanding its capabilities with integrations such as EMR/EHR systems, multilingual support, voice biometrics, and intelligent call routing. 💬 If you're exploring AI solutions for healthcare, I'd love to connect and discuss how conversational AI can modernize patient engagement. #AI #ArtificialIntelligence #HealthcareAI #HealthTech #VoiceAI #AIReceptionist #Automation #ConversationalAI #PatientExperience #GenerativeAI #LLM #Innovation
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Cover image for I just completed a production-ready
I just completed a production-ready AI Lead Generation Agent designed to automate how businesses discover, verify, and export qualified leads across multiple data sources. This system replaces manual lead hunting with an intelligent, filter-driven pipeline that aggregates business data, verifies contact information, and delivers CRM-ready outputs in real time. 🔑 What this agent does: • Searches businesses by location, industry, and keywords • Aggregates data from Yellow Pages, Google Maps (API-ready), and extensible sources • Applies smart filters (company size, founding date, industry relevance) • Automatically verifies emails, phones, and websites • Deduplicates leads for clean datasets • Exports structured CSVs for sales & marketing teams • Supports real-time queries via a FastAPI backend • Schedules daily exports and weekly reports 🧠 Tech Stack Highlights: • Python + FastAPI (async, high-performance backend) • Selenium-based scraping with anti-bot handling • Modular lead source orchestration • Glassmorphism UI with real-time search • CSV-based persistence (lightweight & scalable) This project was built with real business use cases in mind — sales pipelines, outreach automation, and scalable lead discovery — not just experimentation. 🎥 Full walkthrough video: 👉 I’m actively building and sharing end-to-end AI systems focused on automation, data intelligence, and real-world impact. hashtag#AI (https://www.linkedin.com/search/results/all/?keywords=%23ai&origin=HASH_TAG_FROM_FEED) hashtag#ArtificialIntelligence (https://www.linkedin.com/search/results/all/?keywords=%23artificialintelligence&origin=HASH_TAG_FROM_FEED) hashtag#LeadGeneration (https://www.linkedin.com/search/results/all/?keywords=%23leadgeneration&origin=HASH_TAG_FROM_FEED) hashtag#Automation (https://www.linkedin.com/search/results/all/?keywords=%23automation&origin=HASH_TAG_FROM_FEED)hashtag#SoftwareEngineering (https://www.linkedin.com/search/results/all/?keywords=%23softwareengineering&origin=HASH_TAG_FROM_FEED) hashtag#FastAPI (https://www.linkedin.com/search/results/all/?keywords=%23fastapi&origin=HASH_TAG_FROM_FEED) hashtag#WebScraping (https://www.linkedin.com/search/results/all/?keywords=%23webscraping&origin=HASH_TAG_FROM_FEED)hashtag#SaaS (https://www.linkedin.com/search/results/all/?keywords=%23saas&origin=HASH_TAG_FROM_FEED) hashtag#Startup (https://www.linkedin.com/search/results/all/?keywords=%23startup&origin=HASH_TAG_FROM_FEED) hashtag#Entrepreneurship (https://www.linkedin.com/search/results/all/?keywords=%23entrepreneurship&origin=HASH_TAG_FROM_FEED)hashtag#TechProjects (https://www.linkedin.com/search/results/all/?keywords=%23techprojects&origin=HASH_TAG_FROM_FEED) hashtag#AIProjects (https://www.linkedin.com/search/results/all/?keywords=%23aiprojects&origin=HASH_TAG_FROM_FEED) hashtag#BuildInPublic (https://www.linkedin.com/search/results/all/?keywords=%23buildinpublic&origin=HASH_TAG_FROM_FEED)hashtag#BusinessGrowth (https://www.linkedin.com/search/results/all/?keywords=%23businessgrowth&origin=HASH_TAG_FROM_FEED) hashtag#SalesTech (https://www.linkedin.com/search/results/all/?keywords=%23salestech&origin=HASH_TAG_FROM_FEED) hashtag#B2B (https://www.linkedin.com/search/results/all/?keywords=%23b2b&origin=HASH_TAG_FROM_FEED)
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Cover image for Building the Future of Hiring:
Building the Future of Hiring: Real-Time AI Interviews I’m excited to share a demo of our AI-based recruiter automation tool, designed to streamline recruitment funnels with real-time video interviews, deep skill analytics, and cheating detection. In this video, I demonstrate the full candidate journey: 🔹 Backend Automation: The system extracts skills from my resume and matches them against the job description automatically. 🔹 Interactive Interview: I speak directly with "Higher Vision AI" about my experience in Computer Vision, GenAI, and Agentic AI across industries like security surveillance and e-commerce. 🔹 Technical Deep Dives: We discuss real-world challenges, such as implementing voice-to-voice interaction using LiveKit and how I adapted to new integration hurdles. 🔹 Instant Feedback: The session wraps up with a comprehensive dashboard displaying my interview score, resume score, summary, and skills audit. I also discuss how I stay ahead of trends using resources like daily.dev (http://daily.dev). 🎧 Note: Please excuse the slight echo on the agent's voice in this screen recording; it is a result of the recording setup, not the live system! #AgenticAI (https://www.linkedin.com/search/results/all/?keywords=%23agenticai&origin=HASH_TAG_FROM_FEED) #TalentAcquisition (https://www.linkedin.com/search/results/all/?keywords=%23talentacquisition&origin=HASH_TAG_FROM_FEED) #ComputerVision (https://www.linkedin.com/search/results/all/?keywords=%23computervision&origin=HASH_TAG_FROM_FEED) #PeopleAnalytics (https://www.linkedin.com/search/results/all/?keywords=%23peopleanalytics&origin=HASH_TAG_FROM_FEED) #VoiceAI (https://www.linkedin.com/search/results/all/?keywords=%23voiceai&origin=HASH_TAG_FROM_FEED) #FutureOfWork (https://www.linkedin.com/search/results/all/?keywords=%23futureofwork&origin=HASH_TAG_FROM_FEED) #SkillAssessment (https://www.linkedin.com/search/results/all/?keywords=%23skillassessment&origin=HASH_TAG_FROM_FEED) #InterviewIntelligence (https://www.linkedin.com/search/results/all/?keywords=%23interviewintelligence&origin=HASH_TAG_FROM_FEED) #LLM (https://www.linkedin.com/search/results/all/?keywords=%23llm&origin=HASH_TAG_FROM_FEED) #SecureHiring (https://www.linkedin.com/search/results/all/?keywords=%23securehiring&origin=HASH_TAG_FROM_FEED) #TechRecruitment (https://www.linkedin.com/search/results/all/?keywords=%23techrecruitment&origin=HASH_TAG_FROM_FEED)
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Cover image for I wanted to make an
I wanted to make an AI talk to me like a real human. Not a chatbot that waits for you to finish speaking. Not a voice note exchange. I wanted an AI that could listen while I spoke, interrupt naturally, and respond instantly — like a personal assistant or customer-care agent. Something that didn’t just reply, but could actually do things — send emails, check dashboards, automate tasks. So I started small. I used a basic text model with Kokui for speech-to-text. The first time it responded, it felt magical — until it started ignoring me mid-sentence, replying late, or not speaking at all. Latency was awful. It wasn’t a conversation; it was waiting for a robot to remember it existed. I upgraded to DeepGram, tuned the audio, and still, it felt disconnected. I wanted real-time. I wanted the AI to exist in time with me, not after me. So I went deep into research. GitHub, StackOverflow, documentation black holes, even different AI platforms — but nothing gave me the real-time link I needed. Then I found one line buried in a doc: “OpenAI uses LiveKit for real-time voice.” That changed everything. LiveKit works like Zoom — a room where participants join and talk. I built my agent to join a LiveKit room, then I joined as well. And for the first time, I wasn’t sending messages to a server — I was talking to an AI inside the same space. The first test stunned me. Latency dropped to about 50ms. The AI listened while I spoke, and responded instantly. For the first time, it felt alive. Then came a strange bug. The AI joined once, but couldn’t reconnect after leaving. I rewrote code, regenerated tokens, nothing worked — until I realized LiveKit doesn’t let you rejoin a room with the same token. I changed the room name and boom — it worked flawlessly. Now it runs inside LiveKit Sandbox, talking and listening in real-time. It can send emails, check dashboards, handle automation — all with almost zero delay. I started out trying to make a talking AI. What I built feels more like a digital employee — one that works, listens, and speaks in real time. And the best part? It doesn’t feel like the future anymore. It feels like now. #AI (https://www.linkedin.com/search/results/all/?keywords=%23ai&origin=HASH_TAG_FROM_FEED) #ArtificialIntelligence (https://www.linkedin.com/search/results/all/?keywords=%23artificialintelligence&origin=HASH_TAG_FROM_FEED) #LiveKit (https://www.linkedin.com/search/results/all/?keywords=%23livekit&origin=HASH_TAG_FROM_FEED) #VoiceAI (https://www.linkedin.com/search/results/all/?keywords=%23voiceai&origin=HASH_TAG_FROM_FEED) #AITools (https://www.linkedin.com/search/results/all/?keywords=%23aitools&origin=HASH_TAG_FROM_FEED) #MachineLearning (https://www.linkedin.com/search/results/all/?keywords=%23machinelearning&origin=HASH_TAG_FROM_FEED) #AIAssistant (https://www.linkedin.com/search/results/all/?keywords=%23aiassistant&origin=HASH_TAG_FROM_FEED) #AIInnovation (https://www.linkedin.com/search/results/all/?keywords=%23aiinnovation&origin=HASH_TAG_FROM_FEED) #TechDevelopment 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13
FastAPI(1)
Usman Haider's avatar
Usman Haider
Lahore, Pakistan
AI/ML & Data Solutions Engineer
New to Contra
AI/ML & Data Solutions Engineer
Cover image for Developed a full-stack language learning
Developed a full-stack language learning application tailored for Luxembourgish, combining speech recognition, natural language understanding, and generative AI. Fine-tuned OpenAI’s Whisper model for accurate Luxembourgish transcription and built a custom text-to-speech (TTS) engine for realistic audio feedback. A RAG-based architecture enables the app to answer user queries contextually, making learning highly interactive. The frontend is built with React, while Flask powers the backend. Designed to deliver an immersive, conversation-driven auditory learning experience.
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Cover image for Hey Contra! Excited to finally
Hey Contra! Excited to finally be here and connect with builders, founders, and innovators from around the world. I'm Osman, an AI Engineer specializing in AI Agents, LLM Applications, Automation Systems, and Full-Stack Development. Over the past 3+ years, I've helped businesses transform ideas into intelligent products using OpenAI, Gemini, LangChain, LangGraph, FastAPI, Django, and modern cloud technologies. Some of the solutions I've built include: • AI Agents and Multi-Agent Systems • RAG Applications with Private Knowledge Bases • AI-Powered SaaS Products • Automation Workflows with n8n, Zapier, and Make • Voice AI Agents with Twilio and ElevenLabs • Custom Chatbots and Internal AI Tools • Data Automation and Web Scraping Systems I enjoy solving complex problems and building products that create real business value—not just demos. Looking forward to connecting with founders, startups, agencies, and teams working on exciting AI projects. If you're building something ambitious with AI, let's talk.
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Cover image for Retail Knowledge Graph In this project,
Retail Knowledge Graph In this project, we built a semantic knowledge graph tailored to the retail industry. The pipeline involved developing AI agents to transform heterogeneous data into standardized formats. Ontologies were created to represent domain knowledge accurately. Using Gemini models and LangChain, user queries were converted into Cypher queries to retrieve insights from a Neo4j database. We utilized an MCP server for orchestration and LangSmith for secure login and audit trails. This system enhances complex data exploration for non-technical users.
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Cover image for Student Medical Chatbot Built a chatbot
Student Medical Chatbot Built a chatbot to assist MBBS students in navigating medical literature. Leveraged Llama Index and fine-tuned language models to ensure accuracy. Embeddings were stored in OpenSearch, hosted on AWS. The Django backend included secure authentication and session management for a robust user experience.
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FastAPI(2)