Data Engineering Projects in Punjab
Data Engineering Projects in Punjab
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5
Toolshed (Data, Automation, AI Agents, Framer, Retool)
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Development of Financial Management Platform for Vergo
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Umar Abdullah
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Senior Browser Developer | Custom Chromium Browser Development
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5
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Spacebar Technologies
Instacoach
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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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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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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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MFA Faizan
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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Muneeb Bhatti
Shakehand- Ai cold emailing plateform
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Arbab Khan
Earthquake prediction using LSTM
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Tanveer Hussain
RAG Pipeline Implementation
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64
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Afaq Javed
UK B2B Lead Pipeline
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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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Abu Sufyan
Severance Calculator
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Awais Ahmed
KPI Performance Tracker
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Arham Malik
Imagine having over 100 different data sources all over the place. That was the problem Apex Analytics solved. I built this big data platform on Google Cloud using BigQuery and ETL pipelines that clean, transform, and unify everything. The frontend is React based, so stakeholders can see real time KPIs without waiting forever. Queries come back in under a second even with millions of records. It felt like solving a giant puzzle, but the result was a super reliable analytics hub that the entire company trusted. For more details, please visit: https://arham-nexus.vercel.app/work/apexanalytics
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Attaul Mohiman
Challenge is a live fitness platform that transforms health goals into team-based competitions. It combines gamified daily tasks with robust social networking to drive consistent user engagement. Competitive Logic: Organizers can configure 2 or 4 teams and set custom challenge durations. Point System: Users complete daily tasks and questionnaires. Scores are logged and reset to 0 every 24 hours. At the end of the week, the system calculates totals to crown a winning team. Social Ecosystem: Includes private groups, personal chats, and social feeds. Users can publish articles, create custom challenges, and join global fitness events.
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