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You will get Design. Code. MVP in 48 Hours.
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Project details
Project Overview
This fixed-price package is for founders, product leads, or teams who want to go from idea to high quality working prototype in a very short time. Whether you're preparing for a pitch, testing a new product idea, or need an internal proof-of-concept, I will rapidly design, code, and deliver a production-grade MVP with clean, testable code and a scalable architecture.
What’s is mostly included:
✅ Discovery Call (30 mins)
✅ Technical Scoping & Feature Prioritization
✅ UI/UX Skeleton or Wireframes (optional)
✅ End-to-End MVP Build (frontend + backend or backend-only)
✅ Functional Deployment (e.g., FastAPI, Streamlit, or React-based UI)
✅ Source Code + Documentation
✅ 1 Feedback Round + Bug Fixes
Typical MVPs I Build:
AI-powered dashboards or interactive data apps
Python backends with FastAPI for real-time ML or analytics
Automated workflows or data pipelines
Lightweight web tools (e.g., for fintech, healthcare, research)
Who This Is For:
Early-stage founders who need to impress investors
Researchers or analysts who want quick data tools
Innovation teams looking to prototype ideas before scaling
Technical leads who want to outsource the first working version
This fixed-price package is for founders, product leads, or teams who want to go from idea to high quality working prototype in a very short time. Whether you're preparing for a pitch, testing a new product idea, or need an internal proof-of-concept, I will rapidly design, code, and deliver a production-grade MVP with clean, testable code and a scalable architecture.
What’s is mostly included:
✅ Discovery Call (30 mins)
✅ Technical Scoping & Feature Prioritization
✅ UI/UX Skeleton or Wireframes (optional)
✅ End-to-End MVP Build (frontend + backend or backend-only)
✅ Functional Deployment (e.g., FastAPI, Streamlit, or React-based UI)
✅ Source Code + Documentation
✅ 1 Feedback Round + Bug Fixes
Typical MVPs I Build:
AI-powered dashboards or interactive data apps
Python backends with FastAPI for real-time ML or analytics
Automated workflows or data pipelines
Lightweight web tools (e.g., for fintech, healthcare, research)
Who This Is For:
Early-stage founders who need to impress investors
Researchers or analysts who want quick data tools
Innovation teams looking to prototype ideas before scaling
Technical leads who want to outsource the first working version
Machine Learning Tools
Amazon SageMaker, Azure Machine Learning, Caffe, ChatGPT, deeplearn.js, Deeplearning4j, MATLAB, MLflow, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, QlikView, R, scikit-learn, SciPy, Scrapy, SQL, TensorFlow, Tesseract OCR, Theano, XGBoostWhat's included
| Service Tiers |
Starter
$2,000
|
Standard
$4,000
|
Advanced
$7,000
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Musa
Expert AI, ML & Agentic Systems Across Domains
100%
Job Success
Oadby, United Kingdom - 8:14 pm local time
I build software that requires rigorous mathematical depth, AI, ML and/or data analytics expertise, and production-ready deployment capability - the combination most teams need three or more separate specialists for.
Every system I build goes to production. Deployed solutions running real operations across healthcare, legal, finance, maritime, industrial, and scientific applications.
---
## What Sets Me Apart
- Rare Combination: PhD in AI & Systems Engineering + Chartered Mathematician (UK) + 15+ years shipping production systems. I build the ML, and deploy to production - as one person.
- Domain Versatility: I've delivered production systems across radically different industries because my depth is in methodology, not a single vertical. Clients hire me when the problem is hard and needs to actually work.
- Agentic AI Architect: I design and deploy multi-agent workflow systems that autonomously reason, plan, and execute complex tasks across enterprise domains.
- Proven Track Record: 100% client satisfaction on Upwork. Every client has extended, returned, or referred.
---
## Why Clients Choose Me
- "We need three people for this" → I'm one person who architects, builds, and deploys.
- "Our data scientists can't ship" → Every system I build runs in production.
- "This problem is too complex" → I've crossed healthcare, legal, maritime, and industrial domains. Novel problems are my specialty.
---
## Production Deployments (Selected)
### Healthcare & Medical AI
- Surgical segmentation system for a US hospital :- ultrasound vein/artery detection deployed on Nvidia Jetson edge device, used in live surgery
- FDA 510(k) submissions for AI-enhanced medical imaging :- multiple successful clearances at GE Healthcare
- Clinical AI at NHS Barts Health Trust (Europe's largest cardiovascular centre) :- 50,000+ patient records, 88% diagnostic accuracy
- Biomarker risk scoring platform :- 28 health dimensions from 118 blood biomarkers, end-to-end from ingestion to reporting
### Legal AI
- Case analysis system providing lawyer-grade advice - RAG architecture with case law retrieval, deployed and serving clients in Canada
- Document intelligence for contract analysis - 70% efficiency gains for law firm operations
### Maritime & Industrial
- Ship fuel optimisation :- ML model identifying optimal ports based on fuel energy content, not just price
- 6-hour-ahead location prediction :- real-time forecasting using weather and oceanographic parameters for Gulf of Mexico operations
- Industrial process AI :- distillation plant optimisation, hot rolling mill control systems
---
## Technical Depth
- AI/ML: PyTorch, TensorFlow, custom neural architectures, transformers, computer vision, NLP, time-series forecasting, optimisation algorithms
- Production Systems: AWS/GCP cloud deployment, edge devices (Nvidia Jetson), real-time pipelines, microservices, Docker, Kubernetes
- Healthcare Specific: DICOM, HL7 FHIR, EHR integration, biosignal processing, FDA regulatory submissions, HIPAA/PIPEDA/GDPR compliance
- Agentic AI: Multi-agent systems, RAG architectures, LLM integration (Claude, GPT-4), Model Context Protocol
- Mathematical Foundations: Signal processing, Bayesian statistics, causal inference, control theory - deriving solutions from first principles
---
## Credentials
- PhD in AI & Systems Engineering
- Chartered Mathematician (UK) - professional certification requiring rigorous examination
- 20+ peer-reviewed publications in clinical AI and medical imaging
- Multiple FDA 510(k) clearances
- Systems deployed to 200+ hospitals
---
## Industries & Applications
- Primary: Healthcare & Medical Devices (diagnostic AI, clinical decision support, medical imaging, FDA submissions) · Legal Tech (document intelligence, case analysis, contract AI) · Maritime & Logistics (route optimisation, fuel analytics, predictive systems) · Scientific Computing (biosignal processing, risk modelling, complex simulations)
- Secondary: Financial Services (document extraction, risk modelling) · Industrial (process optimisation, predictive maintenance, safety systems) · Aerospace (systems engineering, reliability analysis)
---
## Engagement Model
- Rate: $200–300/hour depending on complexity and engagement length
- Availability: Selective - I take projects where my expertise genuinely matters
- Working Style: Direct communication, clear milestones, results-focused collaboration.
---
## The Bottom Line
If it requires AI, ML, data science expertise, and production deployment across a specialised domain - and it actually needs to work - that's exactly what I do. Let's discuss your challenge.
Steps for completing your project
After purchasing the project, send requirements so Musa can start the project.
Delivery time starts when Musa receives requirements from you.
Musa works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff & Discovery (Day 0)
Schedule a 30-minute discovery call (or async chat) Clarify goals, features, users, and data Confirm project scope and success criteria
Technical Planning
Draft system architecture and feature plan Choose tools, frameworks (e.g., FastAPI, Streamlit) Prepare development environment