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Description
MergeMe integrates GitHub pull requests and GitLab merge requests into Slack, providing a streamlined, continuously updating notification card for each PR/MR. In contrast to the official Slack applications for GitHub or GitLab, which generate a new message for each event, MergeMe updates a single message as the status evolves (such as opened, under review, approved, or merged). Comments made during the review process are displayed as replies in a thread beneath that notification card, ensuring all feedback stays organized.
It supports a range of code hosting platforms including GitHub, GitLab, and self-hosted instances of GitLab. Users can link multiple git sources in one Slack workspace, directing each repository or project to a designated Slack channel, mapping usernames from GitHub and GitLab to Slack users to ensure that @mentions successfully notify reviewers, and utilizing label-based routing to categorize bugs, features, and documentation tasks into separate channels.
The setup process is quick, requiring roughly five minutes: simply connect your Slack account, link your git provider using OAuth, a GitHub App, or a webhook URL for self-hosted versions, and then configure your channel mappings. MergeMe operates solely on webhook payloads and does not access your private source code.
For those on the Free Hobby plan, users can enjoy one channel mapping and up to five users, making it an ideal starting point for teams looking to enhance their development workflow.
Description
Maintain your usual routine while working within Jupyter Notebooks or any Python setting. Just invoke modelbi.deploy to launch your model, allowing Modelbit to manage it — along with all associated dependencies — in a production environment. Machine learning models deployed via Modelbit can be accessed directly from your data warehouse with the same simplicity as invoking a SQL function. Additionally, they can be accessed as a REST endpoint directly from your application. Modelbit is integrated with your git repository, whether it's GitHub, GitLab, or a custom solution. It supports code review processes, CI/CD pipelines, pull requests, and merge requests, enabling you to incorporate your entire git workflow into your Python machine learning models. This platform offers seamless integration with tools like Hex, DeepNote, Noteable, and others, allowing you to transition your model directly from your preferred cloud notebook into a production setting. If you find managing VPC configurations and IAM roles cumbersome, you can effortlessly redeploy your SageMaker models to Modelbit. Experience immediate advantages from Modelbit's platform utilizing the models you have already developed, and streamline your machine learning deployment process like never before.
API Access
Has API
No
API Access
Has API
No
Integrations
GitHub
Yes
GitLab
Yes
Amazon Redshift
No
Databricks
No
Deepnote
No
Google Colab
No
Jupyter Notebook
No
PyTorch
No
Slack
Yes
Snowflake
No
Integrations
GitHub
Yes
GitLab
Yes
Amazon Redshift
Yes
Databricks
Yes
Deepnote
Yes
Google Colab
Yes
Jupyter Notebook
Yes
PyTorch
Yes
Slack
No
Snowflake
Yes
Pricing Details
£5 per developer seat / month
Free for small teams. Forever!
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
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
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
MergeMe
Founded
2026
Country
United Kingdom
Website
mergeme.dev/
Vendor Details
Company Name
Modelbit
Founded
2022
Country
United States
Website
www.modelbit.com
Product Features
Code Collaboration
Audio Conferencing
No
Chat / Messaging
No
Code Review
No
Discussion Threads
No
IDE Integration
No
Remote Control
No
Remote Pair Programming
No
Screen Sharing
No
Video Conferencing
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
