G2

Kumar G.

Associate - Principal

Computer Software

Mid-Market (51-1000 emp.)

1/12/2022

"End to end machine learning & Deep Learning lifecycle management with Allegro AI Trains"

4/5

What do you like best about Allegro AI Trains server?

Allegro AI Trains Server is a powerful solution, especially for Machine and Deep Learning to perform experience management. Below are some of the areas I liked-

1. An OpenSource solution, so you can find the Github repo to start with it.

2. Create GPU clusters in less than 10 minutes.

3. Affordable deployment as per choice in On-prem, Cloud, or hybrid.

4. ML Ops scheduling and orchestration are easy.

5. It automatically captures the entire experiment environment & variables, git information, platform environment(such as python, etc)

6. Reproducibility and improving team collaboration

7. Easy integration via Code Snippets

8. Create robust leaderboards and compare the performers. Review collected by and hosted on G2.com.

What do you dislike about Allegro AI Trains server?

Being an open-source product, we need to check for support for enterprise deployments. The community is still growing, and I believe the contributors will improve the community. Review collected by and hosted on G2.com.

Recommendations to others considering Allegro AI Trains server:

If you are looking for an on-prem or cloud-based solution to boost your AI/ML projects development, try the AAT server first, you'll realize significant advantages. All the best! Review collected by and hosted on G2.com.

What problems is Allegro AI Trains server solving and how is that benefiting you?

Primarily our team is working on different data science projects where we are trying to solve business problems via Data Science technologies such as AI, Machine learning & Deep Learning. Here we need a platform that can be an easy setup for overall experience management for the project. AAT is a good solution as per our requirement as we have seen significant advantages such as creating ML clusters without extensive DevOps effort etc. Review collected by and hosted on G2.com.