Software Alternatives, Accelerators & Startups

SuperAnnotate VS ZenML

Compare SuperAnnotate VS ZenML and see what are their differences

SuperAnnotate logo SuperAnnotate

Empowering Enterprises with Custom LLM/GenAI/CV Models.

ZenML logo ZenML

Create reproducible machine learning pipelines
  • SuperAnnotate Landing page
    Landing page //
    2023-10-10

SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. With advanced annotation and QA tools, data curation, automation features, native integrations, and data governance, we enable enterprises to build datasets and successful ML pipelines. Partner with SuperAnnotate’s expert and professionally managed annotation workforce that can help you quickly deliver high-quality data for building top-performing models.

  • ZenML Landing page
    Landing page //
    2023-10-05

SuperAnnotate features and specs

  • Activity dashboard: yes
  • Configurable workflow: yes
  • Data import/export: yes
  • Performance metrics: yes
  • Real time analytics: yes
  • Third-party integrations: yes
  • Collaboration tools: yes
  • Data visualization: yes
  • Drag and drop: yes
  • Multiple data sources : yes
  • Reporting/analytics: yes
  • Task management: yes
  • Visual analytics: yes
  • Monitoring: yes
  • Real-time monitoring: yes
  • Secure data storage: yes
  • Trend analysis: yes
  • Visual discovery: yes

ZenML features and specs

No features have been listed yet.

SuperAnnotate videos

No SuperAnnotate videos yet. You could help us improve this page by suggesting one.

+ Add video

ZenML videos

Karachi AI : Meetup 12 - MLOPS INTRODUCTION AND DEMO WITH ZENML (URDU/HINDI)

Category Popularity

0-100% (relative to SuperAnnotate and ZenML)
Data Labeling
100 100%
0% 0
Developer Tools
0 0%
100% 100
Data Science And Machine Learning
AI
56 56%
44% 44

User comments

Share your experience with using SuperAnnotate and ZenML. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare SuperAnnotate and ZenML

SuperAnnotate Reviews

Top Video Annotation Tools Compared 2022
In this blog, we’ll quickly explore annotation platforms and the features they offer to help improve the video annotation process. We’ll be looking closely at six big names in the video annotation market: Innotescus, Dataloop, Scale, V7, SuperAnnotate, and Labelbox.
Source: innotescus.io

ZenML Reviews

We have no reviews of ZenML yet.
Be the first one to post

Social recommendations and mentions

Based on our record, ZenML should be more popular than SuperAnnotate. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

SuperAnnotate mentions (1)

  • data-labeling tools comparison
    Ok, so I tried comparing 4 of the better data annotation tools like dLabel.org, CVAT.com, SuperAnnotate.com and Labelbox.com . I tried them all as thoroughly as I could and I probably missed some things so apologies in advance for that! Let me know what I missed in the comment. Btw, I'm Amir and I've worked most of my data-labeling career at dLabel.org. Source: about 3 years ago

ZenML mentions (10)

  • [D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
    Hey everyone! At ZenML, we released today an integration that allows users to train and deploy models from pipelines in a simple way. I wanted to ask the community here whether the example we showcased makes sense in a real-world setting:. Source: about 2 years ago
  • How we made our integration tests delightful by optimizing our GitHub Actions workflow
    As of early March 2022 this is the new CI pipeline that we use here at ZenML and the Feedback from my colleagues -- fellow engineers -- has been very positive overall. I am sure there will be tweaks, changes and refactorings in the future, but for Now, this feels Zen. - Source: dev.to / over 2 years ago
  • Ask HN: Who is hiring? (March 2022)
    ZenML is hiring for a Design Engineer. ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows. We’re looking for a Design Engineer with a multi-disciplinary skill-set who can take over the look and feel of... - Source: Hacker News / over 2 years ago
  • Ask HN: Who is hiring? (January 2022)
    ZenML | Developer Advocate | Full-time | Remote (Europe / UK) | [https://zenml.io](https://zenml.io) Hey! We are an open-source company and the pulse of [ZenML](https://github.com/zenml-io/zenml)'s community is our driving force! ZenML is a MLOps framework to create reproducible ML pipelines for production machine learning use-cases. As a Developer Advocate / 'Tech Evangelist', you will help us fulfil our mission... - Source: Hacker News / over 2 years ago
  • [P] ZenML: An extensible, open-source framework to create reproducible machine learning pipelines
    GitHub: https://github.com/zenml-io/zenml (A star would be appreciated!). Source: over 2 years ago
View more

What are some alternatives?

When comparing SuperAnnotate and ZenML, you can also consider the following products

Labelbox - Build computer vision products for the real world

Attri - Attri helps companies become AI-first organizations with research in the AI field, designing and applying AI processes, platforms, and solutions for success.

V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.

PrimeHub - PrimeHub provides a ready-to-use research and training environment for data scientists to focus on their true productivity in a collaborative environment.

CloudFactory - Human-powered Data Processing for AI and Automation

Katonic MLOps Platform - Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place.​​