QuickShip Studio
Build Production-Ready MVPs in Days, Not Weeks
AI-Powered Prototyping
Zero-to-Live in Hours
Real Backend, Real Fast
Dynamic Scalability
Modular & Maintainable Codebase
Compliance-Ready
from Day One
Applied AI Services
Production-ready AI solutions built to move from idea to impact.
- Applied AI roadmapping for generative and predictive AI use cases
- Enterprise-grade LLM configuration with prompt engineering and RAG workflows
- AI-powered recommendation engines and content summarization automation
- Ethical, compliant AI frameworks designed for regulated environments
- Rapid AI application development with instant, production-ready deployment
Applied AI Capabilities Built for Production
Predictive & Generative AI
AI techniques that predict outcomes from historical data and generate new content or solutions.
General Purpose Machine Learning
Machine learning algorithms and models applicable across multiple tasks and domains.
Data Analysis & Data Visualisation
Identifying patterns, insights, and trends, visualized through charts, dashboards, and reports.
Data Preparation
Preparing data before and after processing to ensure high-quality AI/ML inputs and outputs.
Training | Optimisation | Inferencing
Training AI/ML models, optimizing performance, and deploying for production inference.
RAG Use Cases Solutioning
Building Retrieval-Augmented Generation (RAG) workflows for precise, data-grounded responses.
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Prediction Use
Cases Solutioning
Designing AI workflows to predict business and operational outcomes.
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LLMs Configuration, Fine-Tuning & Deployment
Configuring, fine-tuning, and deploying LLMs for domain-specific and enterprise applications.
MLOps
Implementing MLOps for automated training, deployment, monitoring, and model maintenance.
Benefits of NonStop Applied AI Services
Time-Saving
What used to take 4–6 weeks now takes <5 days
Cost-Effective
Eliminate the need for large dev teams in early stage
Collaborative
AI + human feedback = smoother iteration cycle
Launch-Ready
Real deployable apps, not just mockups or Figma clones
Customizable
Easily extend with custom logic, APIs, or external services
Why Leading Teams Build With NonStop
Engineering That Scales
Enterprise-grade, cloud-native, and AI-enabled engineering that supports growth, security, and compliance from day one.
Built for Real Users
Empathy-driven delivery ensures solutions align with user behavior, team workflows, and measurable business outcomes.
Partnership, Not Projects
Long-term customer retention driven by consistent execution, reliability, and value beyond launch.
Co-Creation for Faster Innovation
Collaborative delivery models that turn ideas into production faster through shared ownership and creativity.
Flexible by Design
Adaptive engagement models that move at the speed of fast-evolving enterprises and startups alike.
End-to-End Ownership
A single partner from prototyping to production, scaling, and optimization, reducing risk and complexity.
Tech Stack
FastAPI
Python
PyTorch
Pandas
Numpy
HuggingFace
Docker
JN
FastText
GCP
Firebase
OpenCV
RabbitMQ
Tensorflow
Next.js
Tailwind CSS
AWS
Azure
Vercel
GitHub
Cursor IDE
Engineering Services Tailored to Your Needs
As a company, NonStop offers full-stack engineering across Software Development, Quality Assurance, DevOps, and Data Engineering.
Backend Development
Designing and implementing server-side logic, APIs, and databases to ensure robust, scalable, and secure backend systems.
Mobile App Development
Developing responsive and user-friendly mobile applications across iOS, Android, and cross-platform frameworks.
Cloud & DevOps
Managing cloud infrastructure, continuous integration & deployment (CI/CD), and ensuring scalable, reliable, and secure operations.
Frontend Development
Creating engaging, functional, and efficient frontend interfaces using modern web technologies.
UI/UX
Designing intuitive user experiences and visually appealing interfaces that enhance usability and engagement.
Security & Audit
Implementing robust security measures, audits, and compliance checks to protect applications and data.
