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What is Maitai?
Maitai actively identifies and corrects inaccuracies in AI outputs in real-time, significantly improving performance and reliability tailored to your specific requirements. We oversee your AI model infrastructure, meticulously customizing it to fit your applications seamlessly. Enjoy fast, reliable, and cost-effective inference without the typical hassles that come with AI management. By tackling potential errors in AI outputs proactively, Maitai intervenes before any adverse effects can emerge, giving you peace of mind that your AI results meet your expectations. You can be assured that you will never encounter an unsatisfactory output. If we detect issues like outages or reduced performance in your primary model, Maitai effortlessly switches to a backup model to maintain continuity. Designed for user-friendliness, Maitai integrates effortlessly with your existing service provider, allowing you to start utilizing it right away without any service disruptions. You have the option to use your own keys or choose ours for added convenience. Maitai ensures that your model outputs consistently align with your expectations while maintaining stable response times and fulfilling requests without fail. With Maitai, you can concentrate on your primary business objectives, free from concerns about the reliability of your AI systems, ensuring a smoother operational flow. In a world where AI performance is critical, having such a dependable solution in place can make all the difference.
What is Azure Chaos Studio?
Improving the resilience of applications can effectively be accomplished through chaos engineering and testing, which entails the deliberate introduction of faults that simulate real outages. Azure Chaos Studio acts as a robust platform for chaos engineering, enabling the detection of hidden issues throughout all phases of development, including production. By intentionally disrupting your applications, you can identify weaknesses and develop solutions to mitigate them before they impact your users. Experiment with your Azure applications by subjecting them to both authentic and simulated faults within a controlled setting, which enhances understanding of application durability. Observe the responses of your applications to various real-world challenges, including network latency, unanticipated storage failures, expired credentials, or even the total collapse of a data center, by utilizing chaos engineering methods. It is crucial to assess your products’ quality in ways that cater to your organization's specific requirements. Adopt a hypothesis-driven approach to bolster application resilience by integrating chaos testing into your CI/CD pipeline, thereby promoting a proactive stance in software development and deployment. This strategic amalgamation not only fortifies your applications but also cultivates a mindset of ongoing improvement and flexibility within your development teams, ensuring they remain equipped to handle future challenges effectively. Ultimately, embracing chaos engineering can lead to a more robust and reliable software ecosystem.
API Availability
Has API
API Availability
Has API
Pricing Information
$50 per month
Free Trial Offered?
Free Version
Pricing Information
$0.10 per action-minute
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
Maitai
Company Website
trymaitai.ai/
Company Facts
Organization Name
Microsoft
Date Founded
1975
Company Location
United States
Company Website
azure.microsoft.com/en-us/products/chaos-studio/
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)