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Oct 10, 2024 4 min read
Navigating Market Trends: Luxe Quality and Lumina Solutions Lead the Way in AI
Platforms:
Web, MobileCountry:
USAImplementation time:
Dec 2022 – presentSubscribe to Our Newsletter
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about company
Lumina Solutions is an innovative technology company specializing in AI solution development that analyzes finance. Their suite of products empowers banks and financial institutions to analyze big data, predict market trends, and point out fraudulent activities.
before
Before the Luxe Quality team joined the project, Lumina Solutions faced several serious challenges:
- Limited system scalability, which prevented handling growing data volumes and increased response times.
- Lengthy development cycles delay the introduction of new features and reduce competitiveness.
- Lack of automated testing leads to critical production errors and negatively impacts user experience.
- Low accuracy of machine learning models in predicting market trends, undermining client trust.
- Data security issues pose risks of confidential information leaks and non-compliance with regulatory standards.
Challenges And Solutions
Luxe Quality provided a team of 3 developers and 2 testers with experience in financial technologies. We are happy to share this experience with you.
Challenges | Solutions |
---|---|
Limited system scalability | Migrated to AWS cloud infrastructure using Amazon EC2 and Amazon S3 services to ensure scalability and reliability |
Lengthy development cycles | Implemented Agile methodology and project management tools like Jira and Confluence to enhance team efficiency |
Lack of automated testing | Developed automated tests using Pytest for the backend and Playwright for UI testing, improving product quality |
Low accuracy of machine learning models | Optimized models using Hyperopt for hyperparameter tuning and implemented more complex algorithms like gradient boosting |
technologies, tools, and approaches
Key technologies employed by the team to address the peculiar demands of both the development and quality assurance processes included:
Programming languages: Python, JavaScript
Frameworks and libraries:
- Backend: Flask
- Frontend: React
- Machine Learning: Scikit-learn, XGBoost, Hyperopt
Databases: PostgreSQL, Redis
Testing tools:
- Automated testing: Playwright, Appium
- API Testing: Postman
DevOps and CI/CD: AWS, Docker, Jenkins
Project management: Jira, Confluence
Development methodologies: Agile, Scrum
features of the project
The project's key feature was developing a sophisticated market trend forecasting system. Historical data analysis uses machine learning algorithms to generate predictions and help clientele make informed investment decisions. With integration into stock exchange APIs, real-time data retrieval can be done, enabling users to react instantly to market changes.
We then introduced an intuitive user interface with interactive charts and data visualization, making analyzing even very complex financial indicators easier. Besides, we integrated a notification system that notifies users when there are dramatic market fluctuations and offers recommendations for actions to be taken in their specific cases.
results
- Agile processes reduced the time to release new updates by 70%, from 4 weeks to 1 week.
- Improved the accuracy of the forecasting financial models by up to 20%, building trust with clients and, hence, improving investment outcomes.
- Processed and fixed over 560 defects, 21 critical to system stability and security.
- Developed over 780 automated test cases, achieving 90% code coverage and reducing production errors.
- Manual testing
- Smoke testing
- Regression testing
- Functional testing
- Automation testing
- Usability testing
- Software development
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