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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 Continual?

Effortlessly create continuously evolving predictive models without the complexities of detailed engineering procedures. Integrate smoothly with your existing cloud data warehouse, making full use of all available data stored in its current location. Share features and deploy sophisticated machine learning models easily by utilizing just SQL or dbt, with the option to enhance capabilities using Python when necessary. Keep predictions neatly organized in your data warehouse to ensure easy access for both your business intelligence and operational systems. Manage features and predictions right within your data warehouse, which removes the need for any extra infrastructure. Build state-of-the-art models that leverage all your data without having to write code or set up complex pipelines. Encourage collaboration between analytics and AI teams thanks to the extensive flexibility offered by Continual's declarative AI framework. As your operations scale, monitor features, models, and policies through a declarative GitOps workflow. Accelerate the model development process with a collaborative feature store and a data-driven approach, while also ensuring smooth communication across teams. This forward-thinking strategy not only streamlines workflows but also promotes a more cohesive environment for deriving insights and achieving successful outcomes. Ultimately, this leads to a more agile response to business needs and an enhanced capacity for innovation.

Media

Media

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
Snowflake
Amazon EMR
Amazon S3
Apache Spark
Apache Zeppelin
DataOps.live
Databricks Data Intelligence Platform
GitHub
Highcharts
JavaScript
Jupyter Notebook
Keras
Plotly Dash
PyTorch
R
SQL
Scala
TensorFlow

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
Snowflake
Amazon EMR
Amazon S3
Apache Spark
Apache Zeppelin
DataOps.live
Databricks Data Intelligence Platform
GitHub
Highcharts
JavaScript
Jupyter Notebook
Keras
Plotly Dash
PyTorch
R
SQL
Scala
TensorFlow

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

Continual

Date Founded

2019

Company Location

United States

Company Website

continual.ai/

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

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Predictive Analytics

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

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