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AI Application Engineer

I Turn Ideas Into Intelligent Applications.

I design, build and ship AI-powered applications, developer tools and complete software experiences across web, desktop and Android.

  • 22Projects documented
  • 14AI applications and experiments
  • 10With public repositories

About

Software that works, not just prototypes.

I'm Muhammad Umar Jamal, a BSCS student and AI application engineer based in Okara, Punjab. I focus on turning ideas into real, usable software.

That means pairing AI capabilities such as language models, retrieval, vision and automation with the engineering around them: backends, interfaces, packaging and deployment.

My work spans AI assistants, document intelligence, computer-vision systems, Android apps, desktop software and low-level systems programming. I lead Group #2 on university projects, and I learn fastest by shipping.

Name
Muhammad Umar Jamal
Brand
MUdevelops
Location
Okara, Punjab, Pakistan
Education
BSCS, University of Central Punjab, Okara Branch (2023–2027)
University role
Group lead, Group #2
Email
Instantregret96@gmail.com
Phone
+92 321-9211464
GitHub
github.com/MUdevelops

AI Engineering

What I can build with AI

Eleven capabilities, each tied to the projects where I've applied it. Use the project buttons to open the case study.

These come from personal and university projects. Some projects are still in progress or experimental, and they are labelled that way.

RAG systems

Documents›Processing›Embeddings›Vector search›LLM›Cited answer

Computer vision

Camera›Detection›Recognition›AI analysis›Application

AI assistants

Voice or text›Intent›AI model›Tools›Action

AI-powered applications

User input›AI processing›Business logic›Output

The layers behind most of my systems

User›Frontend›API / backend›AI orchestration›LLM or vision model›RAG, database, tools›Intelligent output

Projects

Work I've built and shipped

AI applications lead, supported by web, desktop, Android and systems engineering. Every card shows its real status, and repository links go straight to the project.

Skills

Tools I work with

Grouped by where they sit in a system. No percentage bars: the projects above are the evidence.

Languages

Application and systems code.

PythonC++CAssembly (x86)JavaScriptTypeScriptKotlinHTML & CSS

AI and ML

Models and the pipelines around them.

LLM applicationsPrompt engineeringRAGEmbeddingsVector searchComputer visionModel evaluationPyTorch

Backend and data

Services and storage.

FastAPIREST APIsSQLitePostgreSQLChromaDBSupabase

Frontend

Interfaces people use.

ReactNext.jsViteTailwind CSSBootstrapHTML, CSS, JS

Mobile and desktop

Apps that install and run locally.

KotlinAndroidJetpack ComposePySide6Python desktop apps

Tools and systems

Version control, build and networking.

GitGitHubGitHub ActionsNetlifyEmu8086Cisco Packet TracerPyInstaller

Engineering process

How I build AI applications

Architecture, model integration, testing, interface quality and deployment are decided together, not bolted on at the end.

  1. 1

    Understand

    Define the real problem and what “working” means before touching a model.

  2. 2

    Design

    Decide what the model does and what the application around it handles.

  3. 3

    Build

    Connect models, APIs and retrieval to a real backend, data store and interface.

  4. 4

    Test

    Check outputs and behavior on real inputs, not only happy-path demos.

  5. 5

    Ship

    Package, document and deploy so someone other than me can use it.

  6. 6

    Improve

    Use feedback and failures to tighten the next version.

GitHub

The code, in the open

Source for the projects below lives on GitHub. This list works without any network call; live details are added when GitHub responds.

github.com/MUdevelops

AI applications, developer tools, Android, desktop and systems projects.

Checking GitHub for live repository details…

Contact

Let's build something.

I usually reply within a day. Tell me what you're making and where it needs to run.

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