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Nanonets vs UiPath IXP comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Jan 18, 2026

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

Automation Anywhere
Sponsored
Ranking in Intelligent Document Processing (IDP)
1st
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
641
Ranking in other categories
Business Process Management (BPM) (2nd), Robotic Process Automation (RPA) (2nd), Process Mining (1st), Agentic Automation (1st), Business Orchestration and Automation Technologies (1st), AI Legal & Compliance (1st), AI Finance & Accounting (1st), AI Procurement & Supply Chain (1st)
Nanonets
Ranking in Intelligent Document Processing (IDP)
17th
Average Rating
8.0
Reviews Sentiment
2.2
Number of Reviews
2
Ranking in other categories
No ranking in other categories
UiPath IXP
Ranking in Intelligent Document Processing (IDP)
3rd
Average Rating
8.0
Reviews Sentiment
5.1
Number of Reviews
56
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2026, in the Intelligent Document Processing (IDP) category, the mindshare of Automation Anywhere is 3.1%, down from 3.4% compared to the previous year. The mindshare of Nanonets is 1.7%, up from 1.3% compared to the previous year. The mindshare of UiPath IXP is 4.8%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Intelligent Document Processing (IDP) Mindshare Distribution
ProductMindshare (%)
Automation Anywhere3.1%
UiPath IXP4.8%
Nanonets1.7%
Other90.4%
Intelligent Document Processing (IDP)
 

Featured Reviews

Venkat Sivaprakash - PeerSpot reviewer
Management Consultant at Accenture
Has significantly improved document-driven workflows and reduced processing time across finance and HR functions
Automation Anywhere has evolved significantly and upgraded itself to provide agentic AI and AI-based automation solutions for document automation. The product has matured considerably over time. We can create workflows that can call an API. We can include prompts in particular workflows for ChatGPT-related functions, connecting to an LLM and RAG to perform tasks. For document automation, modern features are available to train documents, ensuring high accuracy and repeatability over time. The system is very easy to use. I recently completed a course in document automation, typically designed for people involved in coding and technical aspects. Though I understand coding comprehensively, I don't do actual coding. The course was very accessible. Currently, extensive coding isn't necessary due to the hybrid model incorporating GenAI aspects, low-code, no-code capabilities, APIs, and numerous pre-built objects in Automation Anywhere. The features include GenAI-driven prompting methods and workflow creation capabilities. In these workflows, we can create decision boxes and call APIs without coding. We simply pull objects, drop them, connect them, and add minimal coding when needed. The most crucial aspect isn't coding but rather sizing the automation and fleshing out the details. Automation Co-pilot takes notes and performs automated analysis. It can extract details from videos, summarize conversations, and provide detailed information. During calls, it identifies instructions and performs tasks such as preparing reports and reconciliation. Automation Anywhere can also connect with Microsoft Co-pilot. Through Co-pilot, real-time operations can be executed, allowing direct interaction between vendors and automation through this component.
AK
Senior Rga Developer at a tech vendor with 10,001+ employees
Automation has transformed complex sales order tables into accurate data for our ERP
I have observed that while training Nanonets, we must provide a larger number of examples or documents. When I trained the model, it usually requested around 50 documents as a dataset to train the model. I found this very difficult because business users are not very helpful in providing such a large number of documents; we usually have around two, three, or five. It would be helpful if we could start training the model with limited datasets and then have an option to always improve the model by providing more datasets as we progress through the journey, but it should not be a blocker at the first stage where you need to provide at least 50 samples for a model to train.
Gangadhar Wali - PeerSpot reviewer
Founder and COO at InVibes
Pre-trained models work well, but it is very expensive
We have to do manual validation for some of the things due to the OCR engine not being so accurate. For example, S is read as 5, 5 as S, 2 as Z, and Z as 2. In the case of currency, if one dot is missing, it gives a completely incorrect number. These discrepancies should be fixed because if the OCR itself doesn't work properly, then AI doesn't help with that. When AI is used for training models, the AI Center works precisely, but if the data itself is wrong, we can't do anything. If the extraction of data is proper, it definitely helps. However, 20% errors could be reduced if the OCR engine were better. In future updates, I would like to see better handling of issues such as when a dot is missing in currency, for example, with dollars, it should handle that automatically. It's very expensive. If the volume increases, we can't afford to use Document Understanding. We are thinking of moving to another solution because we are expecting 80,000 to 100,000 invoices.

Quotes from Members

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

Pros

"I like Automation Anywhere's cloud-based nature. You don't need any on-prem infrastructure to host it."
"A process that used to take seven to ten days has now been reduced to half an hour."
"It is easy and simple to use with its drag and drop functionality."
"The organizations where we have implemented AA have seen tremendous benefits achieved in terms of time and cost-saving with the highest quality of deliverables."
"The robust and flexible nature of the product gives it the capability to automate almost all rule-based processes in each and every ERP application that is currently available in the market."
"The overall UI of the tool is so user-friendly that even a beginner can use it easily."
"The management works well."
"We have been able to take resources that have been doing manual work and putting them into more productive work."
"The best features Nanonets offers include their workflow and OCR detection capabilities, which have positively impacted my organization by helping detect edge cases in OCR that require some post-processing or pre-processing and have improved efficiency and reduced errors."
"Nanonets has positively impacted my organization by providing a solution that works for us as developers."
"Document Understanding's best features are the action center and verification mode."
"AI Center is helpful for creating data sets. Machine learning helps with some extraction. The ML extractor gives good results after training."
"UiPath provides a useful feature that allows us to classify documents as invoices or not."
"The most valuable feature in UiPath Document Understanding is the identification of the fields column in the PDF documents."
"The entity-level extraction is very good. The workflow is also very good."
"The most valuable feature is key-value pair and table extraction."
"The solution allows us to continue with vendors whose information comes in correctly and to stop the automation for vendors with many items that are not clearly defined."
"Invoice processing is the most valuable feature. Most of my customers use Document Understanding for invoice processing. That's one of the most common use cases. Typically, each customer starts their RPA journey with the finance department because that's the area where you can see the most benefit."
 

Cons

"Automation Anywhere will sometimes announce releases or updates in their roadmap, and we wait for them, but they do not happen on time or at all."
"I am looking into IQ Bot, but I wanted more out of it. I am dealing with a lot of scanned documents. I want to see if Automation Anywhere can scan client emails for us because our clients send emails with some incidents and issues. We want to see how automation can automatically do the processing and create some structured data or automate bots to get work done."
"I think it is a little bit of an ongoing struggle, because we don't deal with the infrastructure. We have a separate infrastructure team that sorts all that out. So, sometimes there are communication issues just trying to get our internal IT team onboard to run through the installs and that sort of thing. But, definitely with the new cloud version coming onboard, we'll be looking toward going to that. Hopefully it'll resolve some of that friction that comes about through the install process and complexity."
"It may sound a little funny or weird, but one thing that we are thinking is we have to go to various websites and pick up relevant data from various websites using the bot."
"Sometimes, the ESX services will stop. We are working with IT to resolve this, as it's not our fault. Automation Anywhere is stopping the service, and during that time, the bot will be stopped. Right now, we are logging into the client machine and restarting/rebooting them, then restarting the services. As some of our processes run at night, we won't know that the service is down since our processes run 24/7. This issue is then escalated to the manager. This is the current challenge that we are facing, and we would like them to improve this."
"They should do more on the cognitive side."
"Had we had access to the RPA bots in advance, we would have practiced before fully implementing."
"Some things that I do not see as of today are interactive chat or video interface."
"I have observed that while training Nanonets, we must provide a larger number of examples or documents."
"I think Nanonets can be improved as the pricing seems to be a bit high, which is one of the things they should improve."
"I would like to see more integration of artificial intelligence. That's being implemented, but it would be a massive improvement to the solution's document processing. If UiPath achieves intelligent document processing, it will be far better than anything on the market. There are currently some limitations with the fields that could be addressed using a GPT engine. With an integrated AI model, you wouldn't need to create your taxonomy. You would only need to provide some prompts, such as "What is the property name?" It will store that as a variable."
"If the volume increases, we can't afford to use Document Understanding. We are thinking of moving to another solution because we are expecting 80,000 to 100,000 invoices."
"Currently, we have to train multiple templates because the column size and row size change in each PDF."
"This is an expensive solution."
"They could work on the digitizing and classification of documents."
"The documentation should be more clear, or better training should be provided."
"The signature comparison feature of UiPath Document Understanding could be improved."
"The extraction and classification process should be simplified."
 

Pricing and Cost Advice

"Automation Anywhere is expensive."
"We are interested in saving manual engineer man-hours. So far, we have saved $100,000."
"IQ Bots are very costly. It's not a sustainable bot for us as of now. We will look for better, alternate options for that."
"The setup cost depends on multiple factors, so you need to get details before choosing."
"Our annual licensing costs are around $100,000 a year."
"From my experience, I can say that the initial setup cost is easily recovered over a period of time once the bots start running in production."
"We purchase on a bot basis. Our costs are approximately $5,000."
"We have seen a return of investment because it takes less time to market in our current process. I would estimate a times savings between 20 to 30 percent."
Information not available
"We received a 60-day free trial before having to purchase a license to continue using UiPath Document Understanding."
"UiPath Document Understanding is priced high compared to its competition."
"UiPath has a higher upfront cost, but its Document Understanding feature is not a significant additional expense compared to the overall platform."
"UiPath Document Understanding compared to the competitors is high."
"UiPath Document Understanding is expensive, with the basic annual package including 6,000 documents and the next package including one million documents, a huge price difference."
"UiPath's pricing model is complex and based on AI units, which are consumed during model training and use."
"UiPath Document Understanding is considered a bit expensive compared to other options like Microsoft Azure, which can offer similar quality at a more affordable rate."
"Its pricing can be looked into because it is on the higher side for developing economies, such as India, where the cost of labor is a little cheaper compared to advanced technologies."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Construction Company
12%
Manufacturing Company
11%
Computer Software Company
7%
No data available
Financial Services Firm
20%
Manufacturing Company
10%
Computer Software Company
8%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business154
Midsize Enterprise82
Large Enterprise536
No data available
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise11
Large Enterprise26
 

Questions from the Community

How good is Automation Anywhere for RPA processes?
It depends on your use case. Is it simply to automate a couple of processes? Is it to augment a human team? AA is ver...
How good is Automation Anywhere for RPA processes?
From my experience using AA tool, it depends on the applications that you want to automate, because there some applic...
How good is Automation Anywhere for RPA processes?
It is a highly preferred RPA tool. You can check my Automation Anywhere Review to know more.
What needs improvement with Nanonets?
I have observed that while training Nanonets, we must provide a larger number of examples or documents. When I traine...
What is your primary use case for Nanonets?
Nanonets is primarily used for table extraction from native and scanned PDFs. I have implemented Nanonets for sales o...
What advice do you have for others considering Nanonets?
I cannot speak to the exact cost, but I can say Nanonets saved around six hours per day for a business user for a sin...
What is your experience regarding pricing and costs for UiPath Document Understanding?
Both UiPath and Blue Prism are expensive. Customers are trying to move to some other Agentic space because of high pr...
What needs improvement with UiPath Document Understanding?
The challenge is more on handwriting and language-specific document extraction. There is some room for improvement wh...
What is your primary use case for UiPath Document Understanding?
We use it for broker closure, KYC, mortgage processing, and invoice processing as of now. We have about 100,000 invoi...
 

Comparisons

 

Also Known As

Automation Anywhere, Testing Anywhere, Automation Anywhere Enterprise, Agentic Process Automation System (Now Certified for WorkSpaces)
No data available
No data available
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

Google, Linkedin, Cisco, Juniper Networks, DellEMC, Comcast, Mastercard, Quest Diagnostics
Information Not Available
Information Not Available
Find out what your peers are saying about Automation Anywhere, ABBYY, UiPath and others in Intelligent Document Processing (IDP). Updated: May 2026.
902,495 professionals have used our research since 2012.