SAS Model Manager
Reviews
Star rating
Rank in MLOps Platforms
Pros and cons
Pros
- Model Variety
- Model Management
- Analytics
- Problem Solving
- Machine Learning
- Time-Saving
Cons
- Learning Curve
- Expensive
- Limited Customization
- Complexity
- Functionality Limitations
- Integration Issues
Traffic & LLM citations
Source: G2 review data
Key stats
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 27.1% |
| Mid-Market | 15.7% |
| Enterprise | 57.1% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2025 Q2 | 3 | 3.5 |
| 2026 Q2 | 2 | 4.0 |
Satisfaction ratings
What reviewers say
Transforms Model Deployment with Ease
“I use SAS Model Manager for insights and getting relevant data. I like that it helps accelerate model deployment and streamline the MLOPE processes. What I appreciate most is the AI maturity model and how it integrates the people, technology, and process model into a cohesive cyc”
Managing multiple timeseries model
“Model manager allows me to view all my models in a singular place. Allows me to share and collaborate with others in my team”
Easy and Efficient
“My favorite part about Model Manager was the ability to automate processes that would otherwise take a lot more time & energy in just R or Python. For example, the train and validation split of the data is automatically taken care of when running the model pipeline. Same goes fo”