Software Architecture Projects in PunjabSoftware Architecture Projects in PunjabAI 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 I developed MLM Protect https://mlmprotec.com/, a business management platform with an administration dashboard, CRM functionality, product management, reporting, email campaigns, distribution-center management, and commission workflows.
MLM Protec is a business-development and administration platform for managing MLM operations. The system combines member management, product administration, sales reporting, commission workflows, inventory, distribution centers, email campaigns, merchants, and fraud controls in one dashboard.
The application includes:
-Sales and membership dashboards
- Affiliate and customer management
- Administrator roles and departments
- Product catalogs and collections
- Enrollment packages
- Inventory management
- Distribution centers
- Merchant management
- Commission and payout reports
- Country, rank, sales, and fraud reports
- Email templates and broadcasts
- Fraud-management tools
- API integrations
- Responsive administration screens
I can build the frontend, backend APIs, database structure, administrative workflows, and deployment setup for your MLM, CRM, e-commerce, or business-management application.
Skills used
- Full-stack web development
- CRM development
- MLM software development
- E-commerce development
- Admin dashboard development
- Database design
- REST API development
- API integration
- Responsive web design
- State management
- Reporting and data visualization
- Role and administrator management
Tools and technologies
- React
- Redux
- JavaScript
- Node.js
- ExpressJS
- MongoDB
- Spring Data MongoDB
- NGINX
- API integration
- Database design
- Responsive design
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
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(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) I built a B2B lead generation app. You type in an industry and a location, and it finds real businesses through the Google Places API, then enriches them with company data and decision-maker emails via Apollo. Every email gets validated, and GPT-4o-mini writes a short personalized pitch plus a lead score for each lead. One click exports everything to CSV or Excel.
The three API keys are yours. You enter them once in the setup wizard and they stay encrypted on your own machine. Nothing is scraped, no proxies, no LinkedIn tricks, no SMTP probing. The app tells you exactly what each run costs in Google API fees before you spend it, filters out bad-fit leads before any paid enrichment runs, and picks up cleanly if the server restarts halfway.
It ships as a one-click Windows installer and a Docker image. React on the frontend, FastAPI on the backend, JWT auth, and 14 tests green. 
