Projects

Rovo

Rovo

The Ai Experience Management Agent

Rovo is a human-like AI Experience Management Copilot designed to eliminate decision fatigue. It replaces complex menus and dozens of apps with a single, frictionless natural language conversation.

The Problem: Decision Fatigue & App Juggling

Planning an experience—whether a 2-week trip or a simple dinner—is stressful. Users today are overwhelmed by:

  • App Overload → Juggling 10+ apps for research, booking, and navigation.
  • Choice Paralysis → Sifting through thousands of reviews and options.
  • Static Planning → Itineraries that don't adapt when plans change.
  • High Friction → Constant context-switching between screens and menus.

Modern technology has made planning more complex, not simpler.

The Solution: The "Zero-Interface" Guide

Rovo moves beyond being a toolkit to become the guide itself. Using a Team of AI Agents, Rovo plans, adapts, and curates experiences in real-time through a simple chat or voice interface.

Core Capabilities:

  1. Conversational Planning → Plan entire trips, find hidden gems, or book dinner just by asking.
  2. Dynamic Personalization → Rovo learns your travel style and preferences to refine every suggestion it makes.
  3. Real-Time Intelligence → Integrated with web-search and live data for up-to-the-minute flight, hotel, and event info.
  4. Location-Aware Guidance → Hyper-relevant, GPS-based suggestions that guide you while you're on the move.

Why It Stands Out

  • Multi-Agent Orchestration → A proprietary layer that coordinates specialized AI agents to handle complex tasks like itinerary generation and price investigation.
  • Contextual Memory → Rovo remembers past conversations and preferences, making it feel like a personal assistant who truly knows you.
  • Dynamic LLM Allocation → Smart backend logic that chooses the best AI model for each task, minimizing latency and costs without sacrificing quality.
  • Frictionless Experience → No menus. No complex filters. Just a "just ask" experience that minimizes screen time and maximizes the moment.

The Impact (Growth & Scale)

  • 100,000+ Users → Scaled from zero to a massive user base in record time.
  • 20% Retention Rate → High user stickiness in a traditionally low-retention travel category.
  • 84% CSAT Score → Exceptional user satisfaction driven by the human-like interaction model.
  • +6% Conversion Boost → Achieved through rigorous A/B testing and data-driven UX iterations.

How it Works (The "Rovo" Way)

  1. The Ask → Tell Rovo what you're dreaming of: "Plan a romantic 3-day trip to Rome with a focus on hidden pasta spots."
  2. The Curation → Specialized agents search the web, calculate distances, and cross-reference your preferences.
  3. The Interaction → Rovo presents a structured, visual itinerary. You can tweak it, ask questions, or book instantly.
  4. The Journey → While you're traveling, Rovo stays in your pocket, updating your plan based on weather or your current mood.

Technical Highlights

As the Founder & Head of Product, I architected and built the MVP using:

  • Flutter for a high-performance, cross-platform mobile experience.
  • Firebase for real-time synchronization and scalable backend infrastructure.
  • Multi-Agent LLM Orchestration to handle complex, non-linear reasoning.
  • Automated Evaluation Workflows for real-time sentiment analysis and QA.

My Role: From Vision to +100k Users

I led the transformation from VanGo (a travel toolkit) to Rovo (an AI Copilot).

  • Defined the Product Vision → Shifted the focus from "features" to " frictionless experience."
  • Architected the AI Core → Built the proprietary layer that manages multiple LLMs and agents.
  • Led Growth Strategy → Scaled the platform to 100k+ users through data-driven iterations.
  • Managed Full Lifecycle → From initial concept and fundraising due diligence to daily sprint planning.

The result? A paradigm shift in how people plan and live their experiences.

AiAi AgentFlutter+10
Genevous

Genevous

AI-Powered Lead Generation Suite

Genevous turns your website visitors into qualified leads—automatically. No forms. No waiting. No missed opportunities.

The Problem: Traffic Without Leads

You’re spending money on ads and getting traffic. But most visitors leave before you even know who they were.

  • Static pages are boring → Prospects don't want to fill out long forms.
  • Slow follow-ups kill deals → If you don't reply in minutes, they're gone.
  • Zero insights → You have no idea why they didn't buy.
  • Tech is too hard → You don't have months to wait for an IT project.

The gap between traffic and sales is wasting your budget.

The Solution: A Sales Assistant That Never Sleeps

Genevous puts an AI sales expert exactly where it matters most: the moment someone lands on your site. It talks to them, qualifies them, and captures the lead while they’re still interested.

Three ways we help you grow:

  1. GENerate → Your AI Sales Greeter. It engages visitors instantly and qualifies them so your team only talks to "hot" leads.
  2. GENshow → Your Trade Show Copilot. Capture contacts at events using voice or photos and turn them into a structured list instantly.
  3. GENbot → Your Website Brain. A custom assistant that knows your business inside out. It answers questions and closes the gap between "just looking" and "buying."

Why It Actually Works

  • No Coding Needed → You train your AI through a simple chat. If you can send a text, you can set this up.
  • Context is King → Our AI knows if a visitor came from a specific ad. It changes the conversation to match exactly what they were looking for.
  • Always Learning → The more people it talks to, the smarter it gets. It learns which phrases convert and adapts its strategy 24/7.
  • Turnkey Setup → We handle the heavy lifting. You can be live in days, not months.

How It Works (Simple 4-Step Process)

  1. The Brain Dump → You talk to the AI about your business. No technical jargon needed.
  2. The Connection → We link it to your CRM, ads, or website with a few clicks.
  3. The Launch → Your new assistant goes live and starts greeting visitors.
  4. The Growth → You get actionable data and qualified leads delivered straight to your team.

Technical Highlights

I co-planned the strategy and built the MVP from scratch using a modern, scalable stack:

  • Next.js & React for a lightning-fast experience.
  • Firebase for secure, real-time data handling.
  • n8n for powerful backend automation.
  • Notion, Google, & Meta Ads API integrations.

My Role: From Strategy to Code

I write the code and helped shape the product.

  • Co-planned the roadmap to ensure we solved real business pains.
  • Architected the AI layer to keep costs low and quality high.
  • Created the no-code interface so any business owner can use it.
  • Designed for speed, moving from concept to a working MVP in record time.

The result? A platform that makes professional lead generation accessible to everyone.

Aı AgentFirebaseN8N+5
Tilki

Tilki

All-in-One Panel for Private Tutors

Tilki Öğretmen is a comprehensive B2B SaaS management platform designed specifically for private tutors and educators. it replaces the chaos of Excel sheets, WhatsApp messages, and paper notebooks with a single, professional workspace.

The Problem: Administrative Overload

Private teachers often spend more time managing their business than actually teaching. They struggle with:

  • Scheduling Chaos → Juggling dozens of students across different time slots and locations.
  • Payment Friction → Manually tracking who has paid, who is late, and sending awkward reminders.
  • Communication Gaps → Sending repetitive progress updates to parents via WhatsApp.
  • Data Fragmentation → Important student notes and records scattered across multiple apps.

Teachers should be focusing on their students, not on paperwork.

The Solution: Your Teaching Business, Automated

Tilki Öğretmen centralizes every administrative task into an intuitive dashboard. It acts as a digital assistant that handles the "boring" parts of teaching so educators can scale their business without the stress.

Core Capabilities:

  1. Smart Scheduling → A dynamic calendar that manages lessons, recurring slots, and cancellations effortlessly.
  2. Payment Tracking → Real-time monitoring of lesson fees, balance tracking, and automated payment logs.
  3. Parent Communication → professional, one-click progress reports and lesson summaries that build trust and credibility.
  4. Student CRM → A dedicated space for every student’s history, goals, and learning materials.

Why It Stands Out

  • Ecosystem Integration → Part of the wider Tilki.app brand, designed to bridge the gap between AI-powered student coaching and professional teaching management.
  • B2B SaaS Focus → Engineered for high Customer Lifetime Value (CLTV) with a subscription model that provides stable, passive income potential.
  • Mobile-First Design → Built for teachers on the move. Manage your entire student roster from your pocket between lessons.
  • Professional Branding → Elevates a freelancer teacher to a branded business with a consistent, professional appearance.

The Impact (Success Metrics)

  • Market Fit Testing → Currently validating the product-market fit through active landing page conversion tracking and lead generation.
  • Production Ready → Successfully developed and launched the MVP with a dedicated landing page (tilki.app).
  • Time Saved → Automates tasks that typically take 5-10 hours per week for private tutors.
  • Positive Pilot Feedback → Validated through initial testing with active teachers who reported higher parent satisfaction.
  • Scalable Architecture → Designed to be adapted for other service-based industries beyond education.

How it Works (The "Tilki" Experience)

  1. The Validation → We are currently running Meta ads and direct outreach to test conversion rates and gather real-world data.
  2. The Onboarding → Add your students and set your weekly availability in minutes.
  3. The Daily Routine → Check your dashboard to see your day's schedule and unpaid balances.
  4. The Lesson → Log lesson notes and attendance with one tap during or after the session.
  5. The Growth → Send professional summaries to parents and watch your business run like a well-oiled machine.

My Role: From Strategy to Validation

I led the entire Tilki Öğretmen project from the initial "consultative sales" approach to a working SaaS product.

  • Consultative Discovery → Identified the specific pain points of private teachers through direct interviews.
  • Product Strategy → Defined the B2B model to provide financial stability for the Tilki brand.
  • Full-Stack Development → Architected and coded the entire management panel and landing pages.
  • Market Validation → Currently implementing Meta ads and tracking landing page conversions to find the perfect market fit.

The result? A professional tool that helps educators reclaim their time and professionalize their passion.

B2B SaaSNext JsMVP+14
PursuitBot

PursuitBot

Effortless price tracking for Amazon sellers.

PursuitBot is an effortless monitoring system designed specifically for Amazon sellers. It eliminates the "data chaos" of manual price checking by automatically tracking competitor prices and stock status, delivering clear insights through a clean dashboard.

The Problem: Manual Price War Fatigue

Amazon sellers often spend 20+ hours per week manually checking competitor ASINs. They struggle with:

  • Choice Overload → Sifting through endless logs and browser tabs to spot changes.
  • Missed Opportunities → Losing sales because a competitor dropped prices while they weren't looking.
  • Inventory Blindness → Not knowing when a competitor goes out of stock or returns to market.
  • Spreadsheet Hell → Trying to maintain historical trends in messy, manual files.

Sellers should be optimizing their strategy, not refreshing Amazon pages.

The Solution: Autopilot for Competitive Intel

PursuitBot (available at pursuitbot.com) turns raw price checks into actionable signals. It acts as a 24/7 watchtower that records every market move and alerts the seller only when action is needed.

Core Capabilities:

  1. Smart Tracking → Monitors competitor ASINs for price and inventory changes at the frequency you choose (up to 4x daily).
  2. Intelligent Alerts → Automatic email notifications for price drops, stock changes, or "back-in-stock" events.
  3. Visual Analytics → A weekly activity timeline that highlights which brands and categories are most volatile.
  4. Easy Connectivity → One-click exports to CSV, Google Sheets, or Airtable for custom reporting.

Why It Stands Out

  • Multi-Tier Scalability → Designed with flexible plans (Starter, Growth, Scale) to serve everyone from solo sellers to large multi-brand agencies.
  • Signal over Noise → Proprietary logic that tracks "total saved" and margin hints, helping sellers prioritize SKUs that deserve their time.
  • Bulletproof Automation → Built from the ground up to handle thousands of products across multiple sellers with secure data separation.
  • Dead Simple UX → Complex monitoring infrastructure behind the scenes, but a "Set it and Forget it" experience for the user.

The Impact (Real Business Results)

  • 20+ Hours Saved → Weekly manual checking eliminated for every active client.
  • Optimal Pricing → Real-time data allows sellers to match or beat competitor moves within hours, not days.
  • Proven Traction → Currently serving multiple paying clients with a validated subscription model.
  • Market Intelligence → Provides a historical record of competitor positioning that was previously impossible to track manually.

Technical Highlights

As the Lead Architect & Developer, I built PursuitBot's backend using a robust automation stack:

  • n8n for complex workflow orchestration and scheduled Amazon checks.
  • Airtable & Supabase for centralized, high-performance data storage.
  • Render for reliable, cloud-based deployment of the automation engine.

My Role: From Ground-Up Build to Scale

I designed and implemented the entire system to be both powerful and scalable.

  • Architecture Design → Built the multi-tier monitoring engine that serves concurrent clients with different needs.
  • Scraping Strategy → Developed a resilient way to track thousands of ASINs without being blocked.
  • Notification Engine → Created the logic for customizable alerts based on price percentage drops and stock thresholds.
APIsN8NSaaS+5
Kidvo

Kidvo

Parenting & Child Development App

Kidvo is a specialized growth-tracking platform designed to empower parents with data-driven insights. It simplifies the complex journey of early childhood development through an intuitive mobile-first experience.

The Problem: Fragmented Parenting Data

New parents are often overwhelmed by scattered information and manual tracking. Existing solutions are often:

  • Too Complex → Overloaded with unnecessary features that confuse tired parents.
  • Manual Heavy → Hard-to-use interfaces that make frequent logging a chore.
  • Lack of Insights → They track data but don't explain what it means for the child's development.
  • Disconnected → No easy way to share health and growth logs with doctors or partners.

Early parenthood needs clarity, not more complexity.

The Solution: The Digital Growth Companion

Kidvo provides a streamlined, full-stack solution that centralizes every critical metric of a child's development—from physical growth to health milestones—in a single, secure mobile app.

Core Capabilities:

  1. Growth Tracking → Log height, weight, and head circumference with WHO-standard percentile charts.
  2. Health Logs → Keep track of vaccinations, medications, and symptoms in a searchable timeline.
  3. Milestone Mapping → Monitor developmental stages and get age-appropriate tips for every milestone.
  4. Partner Sync → Real-time synchronization so both parents and caregivers stay perfectly aligned.

Why It Stands Out

  • Full-Stack Ownership → I owned the entire product lifecycle, from the first wireframe to the final App Store submission.
  • Seamless Offline-First → Built to work anywhere. Data syncs to the cloud whenever a connection is available, ensuring zero data loss.
  • High Performance → Engineered with a lightweight architecture to ensure instant loading—critical when you have a baby in one hand and your phone in the other.
  • Data-Driven Peace of Mind → Turns raw numbers into visual progress reports that parents can understand at a glance.

The Impact (Success Metrics)

  • Successfully Launched → Delivered a production-ready app to the App Store & Google Play.
  • End-to-End Delivery → Managed concept, design, development, testing, and deployment as a solo developer.
  • High Reliability → Achieved a 99.9% crash-free rate through rigorous automated testing and clean architecture.
  • Positive Market Feedback → Validated the need for a simplified, "less-is-more" approach to parenting tech.

How it Works (The "Kidvo" Experience)

  1. The Quick Log → Snap a photo of a vaccine record or log a feeding in two taps.
  2. The Visualizer → View growth curves and developmental percentiles updated in real-time.
  3. The Shared Brain → Automatically invite partners or grandparents to contribute to the child's digital diary.
  4. The Doctor's Visit → Export a comprehensive health summary to show the pediatrician during check-ups.

Technical Highlights

As the Sole Product Owner & Lead Developer, I built Kidvo using:

  • Flutter for a beautiful, consistent UI across iOS and Android.
  • Firebase for real-time data sync, authentication, and secure cloud storage.
  • Custom Local DB Sync → Developed a proprietary sync layer(SQL Lite & Firestore) to ensure offline reliability.
  • Cloud Functions → Automated periodic health reminders and growth report generation.

My Role: Solo Founder & Architect

I wore every hat to bring this vision to life.

  • User Research → Interviewed parents to identify the "must-have" vs. "nice-to-have" features.
  • Product Architecture → Designed the system to be highly scalable while maintaining strict privacy standards.
  • Mobile Engineering → Wrote every line of code, ensuring a premium, native feel on both platforms.
  • GTM & Publishing → Managed the entire App Store optimization (ASO) and release process.

The result? A trusted digital tool that makes the hardest job in the world—parenting—a little bit easier.

FlutterFirebaseSQL+4
GeoQueryFirestore

GeoQueryFirestore

Advanced Geospatial Queries for Firestore

GeoQueryFirestore is an open-source Dart package that solves one of Firestore’s biggest limitations: performing performant geospatial queries at scale. It enables developers to filter location-based data with support for pagination, limits, and ordering—features often missing in standard solutions.

The Problem: Firestore's Geo-Query Gap

While Firestore is powerful, its native support for location-based searches is limited. Developers often struggle with:

  • No Pagination → Loading thousands of nearby locations at once, causing crashes and high costs.
  • Missing Sort/Limit → Inability to retrieve only the "closest 20" items or sort by a secondary field.
  • Performance Bottlenecks → High latency when querying large datasets using standard geofence methods.
  • Inflexible Ranges → Difficulties in handling custom search radii or map-view boundaries.

Existing tools like GeoFlutterFire provided a start, but couldn't handle production-grade enterprise needs.

The Solution: A Robust Geo-Engine for Dart

GeoQueryFirestore (available on GitHub) operates by intelligently selecting geohash precision based on the search area. It treats location data as a first-class citizen, allowing for complex queries that feel native to Firestore.

Core Capabilities:

  1. Query by Range → Search within a specific radius (e.g., 10km) with automatic precision adjustment.
  2. Map Bounds Search → Fetch only the documents currently visible on a user's map screen (LatLngBounds).
  3. Built-in Pagination → Effortlessly "load more" results as the user scrolls, saving bandwidth and memory.
  4. Order & Limit → Combine location filters with limit() and orderBy() to show the most relevant data first.

Why It’s a Game Changer

  • Scale-Ready → Specifically designed to handle large datasets where loading everything at once isn't an option.
  • Intelligent Precision → Automatically calculates the optimal geohash length to minimize read operations and maximize speed.
  • Developer Friendly → A clean, intuitive API that integrates seamlessly with existing cloud_firestore projects.
  • Customizable → Supports both predefined ranges and custom meter-based search distances.

The Impact (Open Source Contribution)

  • Bridged the Gap → Created a solution for features (pagination/ordering) that the community had requested for years.
  • Optimization → Reduced unnecessary document reads by optimizing how geohash cells are calculated and queried.
  • Public Utility → Provided as a free, open-source package to help Flutter developers build better location-based apps.

Technical Highlights

Built for the Flutter/Dart ecosystem with a focus on performance:

  • Geohash Algorithm for converting coordinates into searchable string prefixes.
  • Custom Precision Logic to balance search accuracy with query performance.
  • Paging Controller logic that automatically tracks document snapshots for seamless "next page" fetches.
  • LatLngBounds Filtering for strict boundary adherence in map-heavy applications.

My Role: Creator & Maintainer

I identified the technical gap while building location-heavy products and decided to build and open-source the solution.

  • Problem Identification → Recognized the scaling issues with existing Firestore geo-libraries.
  • Library Architecture → Designed the core logic for geohash precision and query concatenation.
  • Documentation & Examples → Wrote comprehensive guides to help other developers implement complex geo-features in minutes.

The result? A go-to tool for Flutter developers who need reliable, paginated, and fast location queries in Firestore.

FlutterDartSWE+2
FetchLocalDB

FetchLocalDB

Firestore-to-SQLite Sync Bridge

FetchLocalDB is a performance-focused Flutter package designed to solve one of the biggest challenges in cloud-native mobile development: high operational costs. It acts as an intelligent bridge that synchronizes data between Firestore and a local SQLite database, ensuring apps stay fast, reliable, and budget-friendly.

The Problem: The "Cloud Bill" Bottleneck

Scaling a Firebase-backed app often leads to a surge in document read counts, resulting in expensive monthly bills. Developers typically face:

  • Sky-High Costs → Constant Firestore reads on every app launch drain the budget.
  • Performance Latency → Fetching large datasets over the network causes slow load times.
  • Offline Fragility → Apps that rely purely on the cloud break in low-connectivity areas.
  • Manual Sync Hell → Writing complex, error-prone logic to handle local caching manually.

The Solution: Intelligently Fresh Data

I built FetchLocalDB (available on GitHub) to automate the "delta-sync" process. It ensures your app only fetches new or changed data, treating your local database as the primary source of truth.

Core Capabilities:

  1. Delta Fetching → Automatically identifies the latest local record and only requests newer documents from Firestore.
  2. Smart Synchronization → Handles both new record insertions and background updates to existing local data.
  3. Offline-First Architecture → Provides an instant-load experience by serving data from SQLite while syncing in the background.
  4. Custom Bridge Logic → Support for complex Firestore queries and custom update-checking models.

Why It Stands Out

  • Cost-Engineering Focus → Explicitly designed to minimize document reads, directly lowering your Google Cloud bill.
  • Developer Simplicity → Replaces hundreds of lines of manual sync code with a single, robust SqlLiteFirestoreBridge.
  • Reliability at Scale → Built-in handling for date-based and index-based comparisons to ensure zero data loss.
  • High Performance → Leverages the speed of local SQLite for UI rendering, making the app feel native and snappy.

The Impact (Optimization Success)

  • Bill Reduction → Proven to reduce Firestore read operations by up to 80-90% for data-heavy applications.
  • UX Transformation → Converts "loading..." screens into instant interactions by prioritizing local storage.
  • Open Source Utility → Providing a production-ready tool for the Flutter community to build sustainable startups.

Technical Highlights

Engineered for the Dart/Flutter ecosystem with an emphasis on durability:

  • Bridge Architecture for decoupled communication between local and hosted databases.
  • UpdateModel Logic for cross-referencing hosted hashes with local primary keys.
  • Timestamp Normalization to handle timezone and epoch conversions between SQLite and Firestore.
  • Automated Error Handling for interrupted sync sessions and network failures.

My Role: Creator & Architect

I recognized the financial burden of scaling Firebase apps and developed this package to de-risk growth for independent developers and startups.

  • Problem Identification → Analyzed cloud billing patterns to identify the most expensive read-heavy workflows.
  • Algorithm Design → Designed the delta-sync algorithm that powers the bridge logic.
  • Library Maintenance → Actively maintaining the package and providing documentation for enterprise-grade integrations.

The result? A critical tool for any Flutter developer looking to build high-performance, low-cost mobile applications.

FlutterDartSWE+6
Linkedin-Moodle (School Project)

Linkedin-Moodle (School Project)

Unified Relational Database Architecture

LinkedIn-Moodle is a comprehensive database engineering project that designs a unified relational schema to bridge the gap between professional networking and academic management. It integrates the complex social interactions of LinkedIn with the structured learning environment of Moodle into a single, cohesive system.

The Problem: Disconnected Data Silos

Professional identities and academic achievements often live in separate worlds. Managing this data at scale presents architectural challenges:

  • Complex Relationships → Juggling professional connections, organizational hierarchies, and academic enrollments.
  • Data Fragmentation → Educational milestones (Moodle) aren't natively linked to professional profiles (LinkedIn).
  • Action Tracking → Managing nested interactions like comments on posts, answers to comments, and assignment grades within a single system.
  • Referential Integrity → Ensuring that weak entities (like comments or assignments) remain consistent across thousands of records.

The Solution: A Seamless Data Blueprint

I engineered an Enhanced Entity-Relationship (EER) model that serves as a bridge between career and education. This project provides the architectural foundation for a platform where learning and networking coexist.

Core Capabilities:

  1. Professional Networking Engine → A robust model for users, organizations, and project tracking with a focus on career history.
  2. LMS Integration → Full course management logic, including teacher-student relationships, assignment tracking, and automated grading schemas.
  3. Nested Interaction Logic → Specialized handling of "Likable Content" across posts, comments, and answers to ensure high-fidelity social engagement.
  4. Optimized Mapping → An iterative relational mapping process that transforms complex EER diagrams into high-performance SQL tables.

Why It Stands Out

  • Academic Rigor → Built using advanced database design principles, focusing on normalization and constraint management.
  • Weak Entity Mastery → Implemented sophisticated logic for weak entities (Assignments, Comments, Answers) to prevent orphaned data and maintain system-wide integrity.
  • Iterative Design → The schema evolved through four distinct iterations, ensuring every relationship was stress-tested for scalability.
  • Unified Identity → Creates a "Single Source of Truth" where a user’s SSN links their student identity to their professional profile.

The Impact (Architectural Value)

  • Zero Data Redundancy → Achieved through careful normalization and strategic primary/foreign key mapping.
  • Scalable Blueprint → Provides a production-ready roadmap for developers building EdTech or HR-Tech platforms.
  • High Performance → Designed for efficient querying across deeply nested social and educational data sets.

Technical Highlights

The project focuses on Database Systems Engineering and pure SQL architecture:

  • Enhanced Entity-Relationship (EER) modeling for high-level conceptual design.
  • Relational Mapping to translate visual diagrams into logical schemas.
  • Referential Constraints (CASCADE, NOT NULL) to ensure data durability.
  • SQL Schema Initialization for automated database setup and testing.

My Role: Database Architect

I led the entire lifecycle of the data architecture design.

  • Systems Analysis → Deconstructed the core entities of LinkedIn and Moodle to identify overlapping data points.
  • Conceptual Design → Designed the EER diagram from scratch, handling complex M:N and 1:N relationships.
  • Logic Implementation → Defined the constraints and triggers required to maintain integrity in a social-academic hybrid environment.
  • Documentation → Produced a comprehensive Analysis Report detailing the mapping iterations and system characteristics.

The result? A sophisticated architectural foundation for the next generation of career-first learning platforms.

Database DesignSQLRelational Schema+5