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Description
Citrusˣ offers a comprehensive platform focused on AI transparency and explainability, empowering organizations to uphold trust in their models. Through the web UI and SDK, data scientists can access Summary and Validation pages to evaluate their models' performance, analyze outcomes, and troubleshoot any issues that arise. Meanwhile, data science managers and Chief Data Officers can oversee their teams' progress, benchmark different models, and confirm that key performance indicators (KPIs) are being achieved. Risk officers and Model Risk Managers (MRMs) can utilize the web interface and detailed reports to ensure the models' reliability, evaluate associated risks, and confirm that AI is employed in a responsible and equitable manner in accordance with regulatory standards. Additionally, executives and regulatory bodies can leverage tailored summary reports to assess the robustness and precision of the models, comprehend the rationale behind their decisions, pinpoint potential risks, and guarantee adherence to compliance protocols, ultimately safeguarding the organization against legal repercussions and preserving its reputation in the industry. This multi-faceted approach ensures that all stakeholders are informed and engaged in the AI governance process.
Description
Domino is a comprehensive enterprise AI platform that enables organizations to transform AI initiatives into scalable, production-ready systems. It supports the full AI lifecycle, including data access, model development, deployment, and ongoing management. The platform provides a self-service environment where data scientists can access tools, datasets, and compute resources with built-in governance and security controls. Domino allows teams to build machine learning models, generative AI applications, and intelligent agents using their preferred development environments. It also includes advanced orchestration capabilities to manage workloads across hybrid, multi-cloud, and on-premises infrastructures. Governance features such as model registries, audit trails, and policy enforcement ensure compliance and reproducibility. The platform enhances collaboration by providing a centralized system of record for all AI assets and experiments. Additionally, it helps organizations optimize costs through resource management and usage tracking. Domino is designed to meet enterprise standards for security and regulatory compliance. Ultimately, it empowers businesses to accelerate AI innovation while maintaining operational control and accountability.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2 Trn2 Instances
Apache Zeppelin
Bitbucket
Dask
Flask
GitHub
GitLab
H2O.ai
JupyterLab
MATLAB
Integrations
Amazon EC2 Trn2 Instances
Apache Zeppelin
Bitbucket
Dask
Flask
GitHub
GitLab
H2O.ai
JupyterLab
MATLAB
Pricing Details
No price information available.
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
Citrusˣ
Website
www.citrusx.ai/
Vendor Details
Company Name
Domino Data Lab
Founded
2013
Country
United States
Website
www.dominodatalab.com
Product 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)
Product 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)
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization