No more typing reviews! Try our Samantha, our new voice AI agent.

Deepset AI Platform vs Kore.ai comparison

 

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

Deepset AI Platform
Ranking in AI Customer Experience Personalization
27th
Average Rating
8.0
Number of Reviews
2
Ranking in other categories
AI Finance & Accounting (8th)
Kore.ai
Ranking in AI Customer Experience Personalization
8th
Average Rating
7.8
Number of Reviews
16
Ranking in other categories
AI Agent Builders (7th), AI Security (7th), AI Customer Support (2nd), AI IT Support (7th)
 

Mindshare comparison

As of August 2026, in the AI Customer Experience Personalization category, the mindshare of Deepset AI Platform is 0.7%, up from 0.1% compared to the previous year. The mindshare of Kore.ai is 1.1%, down from 8.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Customer Experience Personalization Mindshare Distribution
ProductMindshare (%)
Kore.ai1.1%
Deepset AI Platform0.7%
Other98.2%
AI Customer Experience Personalization
 

Featured Reviews

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.
Judin Augustin - PeerSpot reviewer
Associate Data Scientist at Guide House
Automation has reduced large call centers and provides real-time outbound support for patients
Kore.ai is a low-code platform, and you do not necessarily have to be an expert in artificial intelligence or generative AI to use this platform. However, if you have that experience, it will be a valuable add-on. The main advantage is that it has almost every kind of plugin available to use, whether for live agents or if you want to use it as a call center. You have real-time capabilities and the most useful plugins available, with almost every kind of model available with configurations. We can configure the ML models and train them. The platform is very user-friendly with explanatory features and a great UI. One significant feature is the live testing platform with Kore.ai. When you are creating a workflow, you have an interactive, real-time testing platform that reflects every change you make. This makes it easy to debug errors or add new features. Additionally, Kore.ai has many different tools and platforms that cater to different needs, whether for a call center, normal workflow, or machine learning workflow, which is really useful. Because of Kore.ai, it was much easier than creating something manually. A low-code platform always helps, and when that platform has this much capability, it provides far more value than manual development. It was particularly helpful for our team that we could create a POC and get that project into production. Kore.ai helped our team build a generative AI outbound calling chatbot, and it truly helped our customers. If you have a hospital with a thousand employees in a call center, you might consider outsourcing. However, with Kore.ai's outbound calling capabilities, you can eliminate the outsourcing part. You do not need a thousand call center employees. You can accomplish this through automation with just one or two employees if people need to switch to agents. This represented a significant cost reduction.

Quotes from Members

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

Pros

"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."
"Kore.ai has positively impacted my organization by being a big money saver because before having our chatbot, the use case was that every time some of our customers needed help, they used to call a number."
"Kore.ai offers multiple support and services, including API integration, webhook integration, and multiple channels, making it easy to design your own layout, integrate with multiple channels and webhooks, deploy quickly, and track any errors that occur, so it is a good way to start and easy to learn."
"Because of Kore.ai, it was much easier than creating something manually, and when that platform has this much capability, it provides far more value than manual development."
"Kore.ai offers many valuable features, particularly its extensive array of connectors, allowing easy integration with various ERP systems and the straightforward implementation of webhooks and APIs."
"Kore.ai helped us integrate a lot through documentation and trial and error, making it straightforward to integrate overall, resulting in a very good experience for first-timers."
"The best feature of Kore.ai is that it is a cost-saving tool because when we use IVR, we have to assign agents at the backend, but using Kore.ai, we can automate all of those functions."
"Kore.ai has positively impacted my organization by simplifying the process of responding to emails and streamlining the workflow, saving me considerable time."
"Kore.ai has positively impacted my organization by helping us build intelligent chatbots and incorporating voice agents, enabling various clients to adopt these solutions, which have been revolutionary for their businesses."
 

Cons

"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."
"In support, the team is not the greatest, but it works."
"I rated Kore.ai eight out of ten because of the potential for these additional improvements."
"In my experience, Kore.ai is not stable."
"I rated Kore.ai an 8 out of 10 because additional features could be added to it."
"To improve Kore.ai, I suggest focusing on more agentic automation, such as offering MCP kind of features with an orchestration layer for use cases."
"I choose 7.5 out of 10 for Kore.ai because a few things already need to be improved, one of which I have mentioned."
"Customer support is where Kore.ai has significant room for improvement. Post-implementation support is a particularly discouraging aspect for me."
"Kore.ai can be improved by enhancing their documentation, which is currently a bit disorganized."
report
Use our free recommendation engine to learn which AI Customer Experience Personalization solutions are best for your needs.
909,725 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Construction Company
42%
Comms Service Provider
13%
Outsourcing Company
7%
Manufacturing Company
5%
Manufacturing Company
12%
Construction Company
12%
Outsourcing Company
9%
Financial Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise3
Large Enterprise14
 

Questions from the Community

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...
What is your experience regarding pricing and costs for Kore.ai?
The experience with pricing, setup cost, and licensing of Kore.ai is that the price is low, and the licensing is also not costly.
What needs improvement with Kore.ai?
I do not have much to add regarding how Kore.ai can be improved since it has been a long time since we last used it. There are other platforms that offer more features, but those come at a higher p...
What is your primary use case for Kore.ai?
In my past organization, I used Kore.ai for one of the projects over a period of approximately six to eight months. Our main use case for Kore.ai involved building a Gen AI plus conversational AI p...
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
Leading banks & Enterprise Companies
Find out what your peers are saying about Deepset AI Platform vs. Kore.ai and other solutions. Updated: July 2026.
909,725 professionals have used our research since 2012.