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Description
DeployRamp eliminates the uncertainty associated with deploying code by automatically encasing your most critical pull request alterations—such as payment processes and database updates—in feature flags, enabling you to launch with assurance. Its AI meticulously analyzes every pull request to identify potentially hazardous modifications, overseeing the complete process, which includes gradual deployment, real-time error tracking, and immediate rollback should issues arise—without requiring a redeployment. Featuring sub-millisecond flag evaluation, compatible SDKs for all primary programming languages, and smooth integration with platforms like GitHub, GitLab, and any CI/CD system, setting it up takes only a few minutes and remains unobtrusive. Moreover, DeployRamp automatically cleans up flags post-full rollout, preventing the buildup of flag debt and eliminating the need for cleanup tasks. It’s ideal for small teams with a free plan available indefinitely, while paid options commence at $79 per month—providing truly self-managing feature flags that streamline your workflow. Additionally, the solution allows teams to focus on developing new features rather than managing technical debt.
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
API Access
Has API
Screenshots View All
No images available
Integrations
GitHub
GitLab
Amazon Redshift
Databricks
Deepnote
Google Colab
Jupyter Notebook
PyTorch
Snowflake
TensorFlow
Integrations
GitHub
GitLab
Amazon Redshift
Databricks
Deepnote
Google Colab
Jupyter Notebook
PyTorch
Snowflake
TensorFlow
Pricing Details
$79/month
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
DeployRamp
Founded
2026
Website
www.deployramp.com
Vendor Details
Company Name
Modelbit
Founded
2022
Country
United States
Website
www.modelbit.com
Product Features
Feature Management
A/B Testing
Entitlement Management
Feature Alerts
Feature Flag / Toggle
Feature Rollout Management
KPI Monitoring
Kill Switch
Multivariate Testing
Product Experimentation
Whitelist Creation
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization