ALO v2
Key Features
The core features of ALO drastically simplify the AI Solution development process and support a wider range of users in leveraging AI technology to solve domain-specific problems. Let's take a closer look at the main features of ALO.
Easy Experiment Environment Setup
ALO provides an environment where AI model experiments can be easily set up using YAML files. It allows users to manipulate various conditions and parameters to conduct effective experiments without deep knowledge of AI models. Even users without expert knowledge of AI can participate in the process of creating and optimizing high-quality AI models.
Efficient AI Solution Development
ALO helps optimize AI Contents through various experiments and evolve them into AI Solutions specialized for specific problems. This includes tuning AI model parameters and supporting the packaging of necessary Python modules, code, and sample data into Docker images for registration with Mellerikat. It minimizes the need for engineering code required to operate AI Solutions, enabling data scientists to focus on AI modeling development. ALO makes the transition from experimentation to operation efficient, simplifying and accelerating the development process.
Pipeline Automation and Optimization
ALO reads AI Contents based on YAML files and uses Git to download the assets needed for ML Pipeline construction, automatically setting up the required ML Pipeline for AI modeling. It executes the ML Pipeline automatically using specified data and modeling parameters, validating and integrating the results according to Mellerikat system requirements. ALO supports efficient model optimization by identifying the optimal model parameters through various experiments.