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Description
Augmeta offers versatile AI companions that bridge the gaps in product and engineering management, significantly enhancing your team's effectiveness without incurring high expenses. By collaborating with these AI peers, you can implement established strategies, frameworks, and insights tailored to your product and engineering tasks. You have the flexibility to create your own assignments while integrating your team and specific context. These AI peers can efficiently handle tasks on your behalf, providing immediate results through seamless interactions. Each task leverages the methodologies, playbooks, and frameworks employed by leading figures in product and engineering. The AI peers are designed to adapt to your team's unique needs, circumstances, and scenarios, ensuring a personalized experience. You can use a simple no-code builder to create new AI-driven and integrated tasks that amplify your team's productivity. This approach brings specialized knowledge directly to your specific situations and challenges. You can engage with AI peers in real-time, no matter your location, allowing you to incorporate your team's templates, best practices, and context. With familiar collaboration features enhanced by AI peers, you can transform the way your team works together and achieves its goals. Overall, Augmeta redefines team collaboration by making advanced resources readily accessible and adaptable.
Description
NCM Intelligent Operations, previously known as Prism Pro/Ultimate, enhances capacity management, identifies performance irregularities proactively, and simplifies operational tasks with assurance. With a user-friendly interface, it allows for effortless optimization of virtualization and infrastructure management through predictive analytics and automation of tasks. Users can streamline daily operations and boost productivity with minimal effort and no coding required. Gain insights into VM performance in real-time, quickly identify anomalies, and implement automated solutions. Understand capacity utilization, forecast to accommodate business needs, and uncover inefficiencies within the system. The solution leverages machine learning techniques to anticipate capacity trends and recommend resource enhancements effectively. When infrastructure anomalies are detected, they automatically initiate alerts and trigger intelligent remediation processes. Rather than relying on a single algorithm, X-FIT employs a diverse range of models competing in a tournament-style format to identify the most effective one tailored for specific environments, ensuring optimized operations and improved outcomes. This innovative approach not only enhances performance but also significantly reduces the time spent on manual oversight.
API Access
Has API
API Access
Has API
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
Augmeta
Country
United States
Website
augmeta.ai/
Vendor Details
Company Name
Nutanix
Founded
2009
Country
United States
Website
www.nutanix.com/products/cloud-manager/intelligent-operations
Product Features
Product Features
Data Center Management
Audit Trail
Behavior-Based Acceleration
Cross Reference System
Device Auto Discovery
Diagnostic Testing
Import / Export Data
JCL Management
Multi-Platform
Multi-User
Power Management
Sarbanes-Oxley Compliance
IT Management
Capacity Monitoring
Compliance Management
Event Logs
Hardware Inventory
IT Budgeting
License Management
Patch Management
Remote Access
Scheduling
Software Inventory
User Activity Monitoring