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SLAB Exchange
LANCER
Lancer :
Ideal for quick, focused engagements
Team: ≤ 2 resources
Duration: ≤ 3 weeks
Indicative Budget: ≤ $3,000 USD*
Use Cases: MVPs, prototypes, simple websites, bug-fix sprints
Indicative Pricing: ~$15–$25/hr per resource*
Growth :
Best suited for growing products or structured builds
Team: 2–5 resources
Duration: Up to 4 months
Indicative Budget: Up to $30,000 USD*
Use Cases: Feature-rich web apps, integrations, custom dashboards
Indicative Pricing: ~$15–$35/hr per resource*
Enterprise :
Tailored for high-scale, complex or long-term initiatives
Team: 5+ resources
Duration: More than 4 months
Indicative Budget: Starts from $30,000+ USD*
Use Cases: End-to-end platforms, SaaS products, compliance-heavy systems
Indicative Pricing: ~$25–$50/hr depending on roles*
(Development)
Project Description
A forward-thinking fintech startup focused on digital asset trading approached Oodles to build a reliable exchange platform from the ground up. Their goal was to provide users with a seamless experience for real-time transactions in a highly secure environment. The team delivered a full-stack solution with integrated backend logic and an intuitive frontend to power a scalable exchange system.
Scope Of Work
The client needed a secure and responsive digital asset exchange system that could handle real-time user interactions and transactions. The engagement focused on full-stack development, including backend logic, API integrations, frontend interface setup, and environment configuration to ensure high performance and security across the application.
Our Solution
To bring the exchange system to life, the development process began with setting up the backend using Django.
Key Features Implemented:
- Secure User Interface: Built with Angular to ensure responsive design and seamless trading experience.
- Modular Backend Logic: Django enabled quick development and reliable handling of exchange transactions.
- GitHub Integration: Codebase was versioned and managed using GitHub for easy collaboration and deployment.
- Environment Isolation: Python virtual environments were used for clean and conflict-free development.
- Optimized Deployment Workflow: Backend and frontend were structured for easy migration and launch.
