#1 most frequent
United States of America
61.5%8 installations of 13
What is Mage AI?
Mage AI is a cloud-native Data Pipeline orchestration platform designed to facilitate the development, deployment, and management of data-intensive applications. The system provides a managed environment for building modular data workflows that integrate with existing cloud infrastructure and AI developer toolchains.
Categories & Use Cases
Who Buys & Uses Mage AI
#2 most frequent
Brazil
7.7%1 installation of 13
#3 most frequent
France
7.7%1 installation of 13
Mage Review
Use Cases and Deployment Scope
Mage helped us with 1. The probability score for uptake of every product is calculated for customers using ML/ Regression models 2. Pick Top customers for a product/Top products for a customer, based on the requirement. 3. Identify popular product combinations using 4. Association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos 5. Alternatively, use fast-selling products as carriers to sell high-margin but low-selling products.
Pros
- Channel sales decomposition.
- Investment vs incremental impact.
- Optimum channel mix.
Cons
- Acquisition Contribution.
- Business Intelligence Reporting.
- Data Destinations.
Most Important Features
- Real-time monitoring.
- Alerting
- Advanced Drill Downs.
Return on Investment
- Business Understanding.
- Data Acquisition and Understanding.
- Data Modeling and Evaluation.
Get your ranking algorithms up and running with no-code tool Maze.
Use Cases and Deployment Scope
We use Mage to setup ranking algorithms in our product wherever needed. We usually have multiple strategies for choosing the right temperature for air conditioners to function on. Depending on the variables inside and outside the room, we use Mage to rank the strategies and choose the best one.
Pros
- Ranking algorithms.
- Cloud-based tool.
- Increase user engagement.
Cons
- Doesn't have support for programming languages like C++
- Doesn't have a whole ecosystem like AWS to go along with.
- More examples and tutorials will be helpful.
Most Important Features
- No-code tool.
- Easily integrate ranking algorithms.
- Cloud-based support.
Return on Investment
- Reduced time to go live.
- Increased the conversion numbers.
- Improved accuracy of our AI models.
Alternatives Considered
Amazon SageMaker, PyTorch on AWS and Cloudera Data Platform
