Skip to main content
TrustRadius
MLReef

MLReef

Overview

What is MLReef?

MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization.Distributed ML Development: - up to 5X in ML development throughput- up to 85% less dependency on internal data science capacity- Distributed workload on…

Read more

Learn from top reviewers

Distributed ML Ops

Rating: 10 out of 10
March 16, 2022
Vetted ReviewVerified User
Distributed Machine Learning Operations is very important for delivering Machine Learning Projects to our customers.
Continue reading
Hans-Michael Hauser
C-Level Executive - Corporate
Founder & CEO
ML Insights AG
MLReef1 year of experience
Log in with LinkedIn to see content from your network
Return to navigation

Pricing

View all pricing
MLReef

MLReef

N/A
Unavailable

What is MLReef?

MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization. Distributed ML Development: - up to 5X in ML development throughput - up to 85% less dependency on internal data science capacity - Distributed workload…

Entry-level set up fee?

  • Setup fee optional
    Optional

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Would you like us to let the vendor know that you want pricing?

1 person also want pricing

Alternatives Pricing

Qlik Sense

Qlik Sense

$20
per month per user (10 user minimum)
What is Qlik Sense?

Qlik Sense® is a self-service BI platform for data discovery and visualization. It supports a full range of analytics use cases—data governance, pixel-perfect reporting, and collaboration. Its Associative Engine indexes and connects relationships between data points for creating actionable insights.

Anaconda

Anaconda

Free
What is Anaconda?

Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and…

Return to navigation

Product Details

What is MLReef?

MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization.

Distributed ML Development:
- up to 5X in ML development throughput
- up to 85% less dependency on internal data science capacity
- Distributed workload on complex data tasks with seamless involvable domain experts
- Higher acceptance of deploye models ad development is a joint task

Q: What is Distributed ML Development?
Distributed Machine Learning development is the process by which the value-added chain is structurally distributed to different actors across the organization to drive efficiency, transparency, quality and to democratize the knowledge and capacity to create Machine Learning.


MLReef Features

  • Supported: AI Modules: Create AI Modules from fully flexible Git repositories
  • Supported: ML Pipelines: Empower everyone to participate in the ML value chain with low/no code
  • Supported: Data Management: Make data processing a collaborative and connected work
  • Supported: Experiment tracking: Run experiments iteratively and with full reproducibility
  • Supported: Nautilus: Host MLReef on any infrastructure - on the cloud or on-premises

MLReef Screenshots

Screenshot of ML Pipeline creation - from fully flexible git repositories to addressable, explorable and easy accessible drag-and-drop elementsScreenshot of A knowledgebase for your organization: ML Projects and AI Modules (scripts)Screenshot of Full version control and transparent experiment trackingScreenshot of Repositories to manage your scripts (SCM) and data (pipelines)Screenshot of Manage your team, groups and projects with access rights and granular permissions

MLReef Video

Fast prototyping with MLReef (Tutorial!)

MLReef Integrations

MLReef Competitors

MLReef Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish

MLReef Downloadables

MLReef Customer Size Distribution

Consumers40%
Small Businesses (1-50 employees)8%
Mid-Size Companies (51-500 employees)24%
Enterprises (more than 500 employees)28%
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews From Top Reviewers

View all reviews
(1-1 of 1)

Distributed ML Ops

Rating: 10 out of 10
March 16, 2022
HH
Hans-Michael Hauser
Founder & CEO
ML Insights AG (Computer Software, 1-10 employees)
Vetted Review
Verified User
MLReef
1 year of experience
Use Cases and Deployment Scope
Distributed Machine Learning Operations is very important for delivering Machine Learning Projects to our customers.
Pros
  • Helps us to take on more client projects
  • Can be used by data analysts as well as casual users
Cons
  • Out of the box support for major cloud vendors
Likelihood to Recommend
Works well if you have to involve different roles in different organizations in a project. Less suited when you have a complex system of custom developed tools
Most Important Features
  • Allowing distributed learning
  • Easy to learn
Return on Investment
  • We can handle 4 to 6 times more projects at the same time with our team
  • We stay engaged with our customers well beyond the project duration
Other Software Used
Return to navigation