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About

Genie Code is an AI agent built for data teams that analyzes, builds, and maintains complex data workflows inside the Databricks workspace. It autonomously plans and executes multistep tasks while adapting to an organization’s data and governance model, with specialized capabilities across data engineering, data science, machine learning, and business intelligence. Grounded in Unity Catalog metadata, semantics, and governance, it can identify authoritative tables, metrics, and assets, understand dependencies across data and AI systems, and respect existing access controls. For data science, Genie Code can find and clean data, explore datasets, test hypotheses, and generate shareable reports. Machine learning workflows include feature engineering, model training and evaluation, deployment, endpoint configuration, and performance tuning. Data engineers can use natural language to automate ETL workloads, optimize queries, and build Spark Declarative Pipelines.

About

Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Data engineers, data scientists, ML engineers, and analytics teams seeking to automate complex data, machine learning, pipeline, and BI workflows

Audience

Large enterprises, data science teams, and IT leaders looking to build, deploy, and կառավար AI systems at scale with strong governance, security, and infrastructure control

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Per user/per year
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 4.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Domino Data Science has the following pros: - Great Customer service. - Flexibility with notebooks and the ability to define your environment as per your needs. - Collaboration is very much easy with this software. - Launches Quickly and easily scalable of Kubernetes infrastructure.

Cons

  • The only cons that I found with this software were that the datasets are not accessible outside the platform. Other than that, this works fine for me.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Databricks
Founded: 2013
United States
www.databricks.com/product/genie/code

Company Information

Domino Data Lab
Founded: 2013
United States
www.dominodatalab.com

Alternatives

No Alternatives

Alternatives

Categories

Categories

Data Science Features

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

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning Features

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

Integrations

Amazon EC2 Trn2 Instances
Amazon SageMaker
Anaconda
Apache Zeppelin
Bitbucket
Dask
Databricks
Flask
GitHub
GitLab
H2O.ai
Jira
JupyterLab
MATLAB
NVIDIA HPC SDK
NVIDIA NGC
NVIDIA RAPIDS
R
SPARK
SQL

Integrations

Amazon EC2 Trn2 Instances
Amazon SageMaker
Anaconda
Apache Zeppelin
Bitbucket
Dask
Databricks
Flask
GitHub
GitLab
H2O.ai
Jira
JupyterLab
MATLAB
NVIDIA HPC SDK
NVIDIA NGC
NVIDIA RAPIDS
R
SPARK
SQL
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