Machine learning has transformed the business landscape by enabling scalable data analysis and data-driven decision-making. However, building the technology stack to turn raw data into actionable insights is no simple task.
Behind every advanced model lies a structured hierarchy of engineering disciplines:
- DevOps forms the foundation, ensuring scalable, reliable, and secure infrastructure.
- Data Engineering processes and transforms raw data into usable formats.
- Machine Learning Engineering builds, deploys, and optimizes models.
- The Business Layer integrates these insights to enhance decision-making, improve products, and drive revenue growth.
This structured approach ensures that AI/ML solutions are not just theoretical models but real-world tools that create tangible business value.