Data Engineering Projects in Punjab
Data Engineering Projects in Punjab
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6
Toolshed (Data, Automation, AI Agents, Buildship, Framer)
max
Construction FP&A & Revenue AI Platform
6
314
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1
Umar Abdullah
max
Senior Browser Developer | Custom Chromium Browser Development
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509
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1
Spacebar Technologies
Instacoach
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12
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1
Taziem Uddin
pro
No More Mondays: $1M+ Traced, Deal by Deal
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7
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0
Arslan Mehmood
AI-Powered PDF Data Extraction My role: AI Data Processing and Extracton Engineer Organizations often struggle to extract structured and useful information from large volumes of unstructured PDF documents. I developed a flexible AI-powered data extraction solution that allows users to define the specific entities and fields they want to retrieve. The system processes different PDF formats, identifies relevant information, and converts it into structured, usable data. The solution reduces manual document processing, improves retrieval accuracy, and can be adapted to different document types and business requirements. A working demo link is attached.
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108
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Advancing Data Solutions
pro
Real-Time Analytics Platform on AWS
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7
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1
Usman Haider
Worked on an RLHF (Reinforcement Learning from Human Feedback) pipeline focused on dataset creation, data annotation, and model evaluation. My role involved designing and curating high-quality prompt datasets, reviewing AI-generated responses, and providing structured feedback based on accuracy, relevance, safety, and helpfulness. Contributed to improving model performance by ensuring consistent evaluation standards and high-quality human feedback for training alignment and refinement.
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158
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1
Muneeb Bhatti
Shakehand- Ai cold emailing plateform
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69
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0
Muhammad Hamza Zaheer
Point cloud to mesh with above ground object segmentation
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91
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1
Muhammad Ahsan Ghani
An AI-powered product research tool that lets users search by niche and discover viral products, top-performing items, suppliers, prices, and market insights from multiple sources.
1
193
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1
Faizan - AI Entrepreneur
FAWAN OS Neural 1: Enterprise Autonomous Swarm Architecture I engineered an enterprise-grade, multi-agent AI infrastructure designed to completely automate mission-critical workflows, eliminate data silos, and guarantee 100% uptime with self-healing capabilities.
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277
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1
Imran Shafiq
Python Web Automation Bot | Selenium Automation & Form Submission Key Features • Automated real-time website monitoring & form submission. • Human-like browser automation using Python & Selenium. • Intelligent page state detection & automatic error recovery. • Session persistence, configurable delays & proxy support. • Packaged as a Windows EXE for easy deployment. Business Value ✔ Eliminated repetitive manual monitoring. ✔ Improved workflow reliability & efficiency. ✔ Reduced downtime with automated recovery. ✔ Delivered scalable Python automation for enterprise workflows.
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31
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0
Tanveer Hussain
RAG Pipeline Implementation
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76
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2
Umaima Iqbal
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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195
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Mirza Umer
The client was losing high-value business leads due to delayed follow-ups and manual data entry across disconnected platforms (CRM, email, and advertising channels). The internal team was spending upwards of three hours a day manually copying lead data, resulting in data fragmentation and an average response time of over 12 hours. The Tech Stack 1. n8n (Advanced Workflow Orchestration). 2. Webhooks & REST APIs (Data Ingestion). 3. PostgreSQL / Airtable (Centralized Data Warehouse). 4. Slack API (Instant Internal Notifications). The Solution. I engineered an autonomous, multi-stage lead processing engine using n8n. The system captures inbound leads via instant webhooks from front-end marketing platforms, normalizes and enriches the data using secondary API lookups, and instantly populates the centralized data warehouse. Simultaneously, the workflow routes the lead based on custom logic (such as budget or region) and fires an immediate, structured notification to the sales team's Slack channel, allowing for a sub-5-minute response time. The Business Impact. The automated pipeline eliminated manual data entry, recovering roughly 15 hours of administrative time per week for the internal team. More importantly, reducing the lead response time from 12 hours down to under 5 minutes directly improved lead-to-opportunity conversion rates by over 30%.
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52
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Awais Ahmed
KPI Performance Tracker
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62
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