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Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages vs XGEN AI comparison

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We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Red Hat Enterprise Linux 9 ...
Ranking in AWS Marketplace
514th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
XGEN AI
Ranking in AWS Marketplace
85th
Average Rating
7.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Md Al-Amin - PeerSpot reviewer
Senior System Analyst at Thakral
Bank projects have gained strong security and reliable performance for critical applications
From my experience as a partner, the biggest advantage of Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages is that it is a stable and reliable product. It is a reliable OS when I am using it for applications because we run middleware software upon the OS, which means if there are problems or security holes in the OS, my applications also face those issues. In that scenario, the stability and security of Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages is commendable. The security policy of Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages is improved, but security measures must still be implemented. After we install the operating system, the customer's bank security team will harden the OS to block any potential breaches or malicious activities. To measure performance with Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages, I assess how much RAM and CPU the background processes are consuming. I can restrict these processes to ensure that minimal background processes run, allowing my application server software and applications to operate better with the available memory and CPU resources.
Rajiv Kedia - PeerSpot reviewer
IT Director at a consultancy with 10,001+ employees
Personalized conversations have boosted engagement but need clearer insights and cleaner data
My experience with using XGEN AI for hyper-personalization is that it is generally very strong, but it needs to be implemented correctly. The way it really works well is that real-time behavior tracking is very fast, allowing you to give better results to your users. The recommendation engine is also very fast. The main point is that you need clean data; if you don't have clean data, it can reduce the impact and sometimes over-personalize, which can be of no use or may have negative implications as users might see repetitive items. The best features XGEN AI offers, in my view, are its strong event tracking capabilities. It can track events, clicks, and views, and it has good product metadata. If you're looking to build a true conversational AI engine, it is the best. My assessment is that it works best when treated as a revenue engine, not just as a feature. You have to tie it to a metric such as conversation and retention to see clear ROIs. What stands out to me most about the event tracking or conversational AI engine in XGEN AI is its conversational AI understanding. With NLPs or with most chatbots or voicebots that you would be building, the biggest struggle point is that they are very deterministic in nature, and they don't let you know what to tell and when to tell the user. With XGEN AI, I feel this is consolidated and you get a unified view. XGEN AI has positively impacted our organization by helping us track what users are looking for. The initial release itself showed that the success rate is more than what we were getting previously. We were able to collect a lot of data, and the best part is that it can work across channels, apps, and emails, which helps us provide a unified experience to the end user. We have seen XGEN AI recommendations lift conversion by 10 to 15 percent. We have experienced real-time behavior tracking and have started seeing some ROIs; though I'm not allowed to share the actual ROI itself, we see improvement in the overall metrics. User engagement has been very positive. We have focus groups and are collecting client feedback, and for most people that we have been able to capture feedback from, the CSAT has improved. That's the biggest thing, so overall, it's trending towards positive.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Cloud integration is quite easy, and containerization support along with file system level enhancements has improved considerably."
"From my experience as a partner, the biggest advantage of Red Hat Enterprise Linux 9 (redhat 9) | Support by SupportedImages is that it is a stable and reliable product."
"We have seen XGEN AI recommendations lift conversion by 10 to 15 percent."
"We have seen a positive ROI with XGEN AI, as it has helped us save roughly fifteen to twenty percent of development time on coding, debugging, and documentation tasks, allowing the team to focus more on higher-value tasks."
 

Cons

"Regarding the technical team of Red Hat, I find the support to be a mixed bag. In my region during office hours, calls go to the Asia Pacific support team, which is not up to the mark."
"There is room for improvement regarding response time and first-level support quality."
"An area for development with XGEN AI is providing more features for complex or project-specific code, better analysis across multiple codebases or services, and deeper integration with the development tools would make it even more useful for day-to-day work."
"However, the things that do not work as well include its high dependency on data quality and very limited transparency in how recommendations are generated, which needs to improve."
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Top Industries

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Construction Company
26%
Comms Service Provider
25%
Manufacturing Company
11%
Outsourcing Company
8%
 

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Questions from the Community

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What is your experience regarding pricing and costs for XGEN AI?
My experience with pricing, setup cost, and licensing is that it is in line with other similar providers we have used. I would say pricing is comparable, and the licensing is based on subscription ...
What needs improvement with XGEN AI?
One of the improvements I would suggest for XGEN AI is the use of hybrid models and asking real quality questions to the users. Additionally, product attributes or data quality needs to be improved...
What is your primary use case for XGEN AI?
Primarily, our use case for XGEN AI is to advise clients on how to use AI for conversational chatbots. A specific example of how I have used XGEN AI in my work is that we have advised clients on AI...
 

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