Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud BigQuery Reviews & Ratings
    2,008 Ratings
    Company Website
  • Teradata VantageCloud Reviews & Ratings
    1,105 Ratings
    Company Website
  • Gemini Enterprise Agent Platform Reviews & Ratings
    961 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    11 Ratings
    Company Website
  • Windsurf Editor Reviews & Ratings
    168 Ratings
    Company Website
  • SciSure Reviews & Ratings
    298 Ratings
    Company Website
  • AthenaHQ Reviews & Ratings
    34 Ratings
    Company Website
  • RunPod Reviews & Ratings
    205 Ratings
    Company Website

What is Zepl?

Efficiently coordinate, explore, and manage all projects within your data science team. Zepl's cutting-edge search functionality enables you to quickly locate and reuse both models and code. The enterprise collaboration platform allows you to query data from diverse sources like Snowflake, Athena, or Redshift while you develop your models using Python. You can elevate your data interaction through features like pivoting and dynamic forms, which include visualization tools such as heatmaps, radar charts, and Sankey diagrams. Each time you run your notebook, Zepl creates a new container, ensuring that a consistent environment is maintained for your model executions. Work alongside teammates in a shared workspace in real-time, or provide feedback on notebooks for asynchronous discussions. Manage how your work is shared with precise access controls, allowing you to grant read, edit, and execute permissions to others for effective collaboration. Each notebook benefits from automatic saving and version control, making it easy to name, manage, and revert to earlier versions via an intuitive interface, complemented by seamless exporting options to GitHub. Furthermore, the platform's ability to integrate with external tools enhances your overall workflow and boosts productivity significantly. As you leverage these features, you will find that your team's collaboration and efficiency improve remarkably.

What is Modelbit?

Continue to follow your regular practices while using Jupyter Notebooks or any Python environment. Simply call modelbi.deploy to initiate your model, enabling Modelbit to handle it alongside all related dependencies in a production setting. Machine learning models deployed through Modelbit can be easily accessed from your data warehouse, just like calling a SQL function. Furthermore, these models are available as a REST endpoint directly from your application, providing additional flexibility. Modelbit seamlessly integrates with your git repository, whether it be GitHub, GitLab, or a bespoke solution. It accommodates code review processes, CI/CD pipelines, pull requests, and merge requests, allowing you to weave your complete git workflow into your Python machine learning models. This platform also boasts smooth integration with tools such as Hex, DeepNote, Noteable, and more, making it simple to migrate your model straight from your favorite cloud notebook into a live environment. If you struggle with VPC configurations and IAM roles, you can quickly redeploy your SageMaker models to Modelbit without hassle. By leveraging the models you have already created, you can benefit from Modelbit's platform and enhance your machine learning deployment process significantly. In essence, Modelbit not only simplifies deployment but also optimizes your entire workflow for greater efficiency and productivity.

Media

Media

Integrations Supported

Amazon Redshift
GitHub
Jupyter Notebook
PyTorch
Snowflake
TensorFlow
Amazon Athena
Amazon EMR
Amazon S3
Apache Zeppelin
DataOps.live
Databricks
Deepnote
GitLab
Google Colab
JavaScript
Keras
Plotly Dash
Python
SQL

Integrations Supported

Amazon Redshift
GitHub
Jupyter Notebook
PyTorch
Snowflake
TensorFlow
Amazon Athena
Amazon EMR
Amazon S3
Apache Zeppelin
DataOps.live
Databricks
Deepnote
GitLab
Google Colab
JavaScript
Keras
Plotly Dash
Python
SQL

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zepl

Date Founded

2016

Company Location

United States

Company Website

www.zepl.com/product/

Company Facts

Organization Name

Modelbit

Date Founded

2022

Company Location

United States

Company Website

www.modelbit.com

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Popular Alternatives

Popular Alternatives