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Azul Zing vs Deepset AI Platform comparison

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Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

Azul Zing
Ranking in AI Customer Experience Personalization
24th
Average Rating
9.6
Reviews Sentiment
5.9
Number of Reviews
10
Ranking in other categories
Application Infrastructure (12th)
Deepset AI Platform
Ranking in AI Customer Experience Personalization
29th
Average Rating
8.0
Number of Reviews
2
Ranking in other categories
AI Finance & Accounting (9th)
 

Mindshare comparison

As of October 2026, in the AI Customer Experience Personalization category, the mindshare of Azul Zing is 0.9%, down from 13.8% compared to the previous year. The mindshare of Deepset AI Platform is 0.7%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Customer Experience Personalization Mindshare Distribution
ProductMindshare (%)
Azul Zing0.9%
Deepset AI Platform0.7%
Other98.4%
AI Customer Experience Personalization
 

Featured Reviews

Mohakhan Khan - PeerSpot reviewer
Software Technical Expert at a tech vendor with 10,001+ employees
Real-time charging has stayed consistent and cuts GC incidents while reducing cloud costs
The best features Azul Zing offers include no stop-the-world during the full GC. No stop-the-world pauses during full GC, and we hit higher TPS with fewer JVMs -- a real win for maintenance and cost. As an online charging system, we can't afford crashes or latency spikes. Before Zing, JVMs would hang and drop from the grid on missed heartbeats. GC tuning is also out-of-the-box -- no more time consuming manual tuning like with Oracle/OpenJDK with no significant outcome.
CH
Gen Ai Engineer at extend 7.ai
Pipeline framework has transformed how I evaluate RAG models and optimize vector search
The best feature Deepset AI Platform offers is the pipeline feature that is very easy for me to compose the large language model as well as the vector database search and retrieval, allowing me to build the application and the evaluation script within a very short period of time. The pipeline feature and the ease of composing with large language models and vector search save me a lot of time by not writing the code from scratch. I just build the pipeline because Deepset AI Platform provides the out-of-the-box integration with the tools and stack that I am using, including the OpenAI model as well as the Pinecone API. I do not need to implement the details; I just use the existing tools in Haystack, pulling it together for the pipeline. This allows me to avoid too much detailed coding and saves me a lot of work, enabling me to focus on the evaluation. Deepset AI Platform positively impacts our organization because we previously did not use any framework for Gen AI applications, and the introduction of this stack provides a framework for our team. It lets our team think about it and shows that it is worth introducing a framework in the future.

Quotes from Members

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

Pros

"After using Azul Zing, it is almost a zero-incident situation because of the GCs."
"Performance of the JVM, especially the C4 Pauseless Garbage Collection, for continuous application execution is the most valuable feature."
"GC Pause times are maintained in low milliseconds, which is beneficial for applications with high volume, high memory allocation rate, and a high memory footprint, and it also increases throughput by approximately 20-25% as compared to Oracle Java Development Kit based on some tests that I have done with real applications."
"With minimal effort, Zing has helped us improve our latency performance drastically."
"With Zing, we've now been able to re-allocate those tuning resources to general product development."
"With minimal effort, Zing has helped us improve our latency performance dramatically."
"No other JVM on the market even comes close to competing with the Azul Zing."
"The non-stop garbage collector (C4 - Continuously Concurrent Compacting Collector) is the most valuable feature."
"The best feature Deepset AI Platform offers is the pipeline feature that is very easy for me to compose the large language model as well as the vector database search and retrieval, allowing me to build the application and the evaluation script within a very short period of time."
"Specific outcomes since using Deepset AI Platform include ROI from fewer unsupported AI answers, faster context retrieval, and better manager trust in our quality answers."
 

Cons

"We have encounter stability issues and that has been a source of frustration at times."
"It is extremely expensive."
"Although Azul claims to have a fast warmup, we still experience higher latency for the first trade when our system starts up on Sundays."
"However, like every other great product, there is always something that can be improved."
"The licensing over non-production environments considerably affects the cost of our solution as a software vendor."
"The profiling tools included with Zing lag behind those available for Oracle's Java implementation."
"Although Azul claims to have a fast warmup, we still experience higher latency for the first trade when our system starts up on Sundays."
"Deepset AI Platform's accuracy and reliability of output are very good when the pipeline is simple and the data is already clean. However, when the data is not clean and the pipeline is complex, the quality and reliability of Deepset AI Platform decrease."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Manufacturing Company
12%
Construction Company
11%
Comms Service Provider
8%
Construction Company
37%
Comms Service Provider
17%
Outsourcing Company
10%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise4
Large Enterprise3
No data available
 

Questions from the Community

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What needs improvement with Deepset AI Platform?
Deepset AI Platform can be improved by simplifying pipeline management and providing easier debugging for complex Retrieval-Augmented Generation flows. To improve my experience with Deepset AI Plat...
What is your primary use case for Deepset AI Platform?
My main use case for Deepset AI Platform is utilizing it as an AI orchestration layer for RAG, search, and agentic workflows. I use this as an AI orchestration solution for GenAI applications and f...
What advice do you have for others considering Deepset AI Platform?
My advice for others looking into using Deepset AI Platform is to know your use cases. There are many options in the market including LangChain, LlamaIndex, and Pinecone Assistant. It is crucial to...
 

Overview

 

Sample Customers

Priceline, RBS, Credit Suisse, ING, Creditex, Nielsen, Workday, Saks Fifth Avenue, Entergy, Quotix, Puma and many more.  Visit azul.com for more.
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Find out what your peers are saying about Azul Zing vs. Deepset AI Platform and other solutions. Updated: September 2026.
915,341 professionals have used our research since 2012.