Skip to main content
TrustRadius
Mage

Mage

Overview

What is Mage?

Mage is a tool that helps product developers use AI and their data to make predictions. Use cases might be predictions for churn prevention, product recommendations, customer lifetime value and forecasting sales.

Read more

Learn from top reviewers

Mage Review

Rating: 9 out of 10
December 6, 2022
IncentivizedVetted ReviewVerified User
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 produc...
Continue reading
Verified user
Account Manager
Mage3 years of experience

Get your ranking algorithms up and running with no-code tool Maze.

Rating: 8 out of 10
December 3, 2022
IncentivizedVetted ReviewVerified User
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...
Continue reading
Verified user
Contributor
Mage2 years of experience
Log in with LinkedIn to see content from your network
Return to navigation

Pricing

View all pricing

Hobby

$0

Cloud
per user

Pro

$2,000

Cloud
per month per user

Entry-level set up fee?

  • Setup fee optional
For the latest information on pricing, visithttp://mage.ai/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
Return to navigation

Product Demos

Lost Ark Sorceress Endgame Gameplay Demo | Mage | Reflux Build

YouTube
Return to navigation

Product Details

What is Mage?

Mage is a tool that helps product developers use AI and their data to make predictions. Other features include churn prevention, product recommendations, customer lifetime value and forecasting sales.

Mage Competitors

Mage Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Mage is a tool that helps product developers use AI and their data to make predictions. Use cases might be predictions for churn prevention, product recommendations, customer lifetime value and forecasting sales.

Mage starts at $0.

EasyProf, Course Merchant, and dominKnow | ONE are common alternatives for Mage.

The most common users of Mage are from Enterprises (1,001+ employees).
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(3)

Reviews

(1-2 of 2)
Companies can't remove reviews or game the system. Here's why

Mage Review

Rating: 9 out of 10
Incentivized
December 06, 2022
Verified User
Vetted Review
Verified User
Mage
3 years of experience
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 and Cons
  • Channel sales decomposition.
  • Investment vs incremental impact.
  • Optimum channel mix.
Likelihood to Recommend
Mage is well-suited for probability score for uptake of every product is calculated for customers using ML/ Regression models, choosing customers for a product/ Top products for a customer, based on the requirement and Identifying popular product combinations using association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos.
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.

Rating: 8 out of 10
Incentivized
December 03, 2022
Verified User
Vetted Review
Verified User
Mage
2 years of experience
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 and Cons
  • Ranking algorithms.
  • Cloud-based tool.
  • Increase user engagement.
Likelihood to Recommend
Mage is well suited in scenarios where you have to rank AI algorithms based on different parameters. However, Mage does not help you to develop individual algorithms to solve the problem at hand. Also, Mage is a no-code tool, so it makes it easy for product developers to integrate ranking algorithms.
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
Mage was the easiest in terms of ease of implementation due to its no-code functionality. However, Mage doesn't have a whole ecosystem like AWS and slightly falls behind there.
Return to navigation