Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Kaizen Framework is an efficient low-code tool designed for rapid application development, allowing users to create web applications in a matter of minutes. It significantly reduces development costs and minimizes reliance on developers, eliminating the need for coding, compilation, and downtime for users. True to its name, "Kaizen," the framework is consistently updated to ensure that you can maximize your profitability in software development projects. As a mature option among various low-code frameworks, Kaizen has demonstrated its effectiveness by delivering a wide range of applications across multiple industries. Over the past 15 years, it has evolved continuously, resulting in the successful execution of over 500 projects in more than 70 different sectors, providing highly practical solutions. Additionally, it is user-friendly, making it straightforward to learn and deploy, with the flexibility to host applications wherever you choose. With advanced features that set it apart from competitors, the Kaizen Framework is an ideal choice for those looking to streamline their development process.
Description
Developing machine learning applications should be effortless and seamless. UnionML is an open-source framework in Python that enhances Flyte™, streamlining the intricate landscape of ML tools into a cohesive interface. You can integrate your favorite tools with a straightforward, standardized API, allowing you to reduce the amount of boilerplate code you write and concentrate on what truly matters: the data and the models that derive insights from it. This framework facilitates the integration of a diverse array of tools and frameworks into a unified protocol for machine learning. By employing industry-standard techniques, you can create endpoints for data retrieval, model training, prediction serving, and more—all within a single comprehensive ML stack. As a result, data scientists, ML engineers, and MLOps professionals can collaborate effectively using UnionML apps, establishing a definitive reference point for understanding the behavior of your machine learning system. This collaborative approach fosters innovation and streamlines communication among team members, ultimately enhancing the overall efficiency and effectiveness of ML projects.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
No
Google Cloud Platform
No
Microsoft Azure
No
Python
No
Integrations
Amazon Web Services (AWS)
Yes
Google Cloud Platform
Yes
Microsoft Azure
Yes
Python
Yes
Pricing Details
$10 USD per user per day
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
Yes
Windows
Yes
Mac
No
Linux
Yes
Chromebook
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Virtual Splat Software
Founded
2000
Country
India
Website
kaizenframework.app/
Vendor Details
Company Name
Union
Founded
2021
Country
United States
Website
www.union.ai/unionml
Product Features
Low-Code Development
AI-Assisted Development
No
Business Process Automation
No
Collaborative Development
No
Data Aggregation and Publishing
No
Deployment Management
No
Drag & Drop
No
Integrations Management
No
Iteration Management
No
Performance Monitoring
No
Requirements Management
No
Templates
No
Visual Modeling
No
Web / Mobile App Development
No
Workflow Management
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No