Audience

The target audience for NetApp AIPod includes businesses and organizations seeking scalable, high-performance infrastructure solutions to accelerate AI development, streamline workflows, and integrate seamlessly with hybrid cloud environments

About NetApp AIPod

NetApp AIPod is a comprehensive AI infrastructure solution designed to streamline the deployment and management of artificial intelligence workloads. By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and inference, while ensuring robust data management and security. With preconfigured infrastructure optimized for AI tasks, NetApp AIPod reduces complexity, accelerates time to insights, and supports seamless integration into hybrid cloud environments.

Pricing

Free Trial:
Free Trial available.

Integrations

Ratings/Reviews

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Company Information

NetApp
Founded: 1992
United States
www.netapp.com/artificial-intelligence/aipod/

Videos and Screen Captures

NetApp AIPod Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Live Online
In Person
Videos
Support
Phone Support
24/7 Live Support
Online

NetApp AIPod Frequently Asked Questions

Q: What kinds of users and organization types does NetApp AIPod work with?
Q: What languages does NetApp AIPod support in their product?
Q: What kind of support options does NetApp AIPod offer?
Q: What type of training does NetApp AIPod provide?
Q: Does NetApp AIPod offer a free trial?

NetApp AIPod Product Features

Artificial Intelligence

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

Data Management

Information Governance
Data Analysis
Data Migration
Data Quality Control
Master Data Management
Customer Data
Data Integration
Match & Merge
Data Capture
Data Security

Deep Learning

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