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Dify vs Private AI 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:
 

ROI

Sentiment score
5.4
Dify's open-source automation saved time and money, enhancing productivity by transforming manual tasks and testing concepts efficiently.
Sentiment score
5.1
Private AI yielded varied results; significant returns were tied to high investments, while benefits varied with costs and usage.
If a task would require an hour, it can now be done in seconds.
Software Engineer at Futurescape Technologies
This results in cost saving and time saving, as whenever you save some time, that is equal to cost saving.
AI Consultant at AI Solution.dk
It was time-saving because the APIs were faster than our in-house solution.
AI Consultant at a tech vendor with 10,001+ employees
If I buy my own hardware for my organization and I don't need to spend hundreds of thousands of dollars to do that, I'm going to be able to get my ROI back pretty quickly.
AI Strategy & Edge Computing Specialist at Kestrel Partners Group
We achieve tasks that we are supposed to do in a week within a day.
Senior Manager, Automation at a tech services company with 1,001-5,000 employees
Time saving is implemented by using AI.
Senior Executive at a insurance company with 5,001-10,000 employees
 

Customer Service

Sentiment score
5.0
Dify's customer support is praised for instant, efficient service through attentive agents and effective feedback implementation, achieving high ratings.
Sentiment score
6.5
Private AI customer service is praised for fast, tailored support but open-source users don't use it; satisfaction is high overall.
I have been impressed by the voice agent, the feedback the team requests, and the developments they have implemented so far.
AI AUTOMATION ENGINEER at a consultancy with 51-200 employees
Whenever you have questions, you get an instant answer.
AI Consultant at AI Solution.dk
I already understood how to use user input, the LLM model, and templates without needing guides.
Student at Sector 125
We have a contract with the client in order to manage scalability, durability, and continuity of service.
Head of Data & Analytics Department Senior Software Engineer at a tech services company with 501-1,000 employees
Because Private AI is deployed by our company, the support is also very good.
Senior Project Analytics Consultant And Senior Manager Enterprise Portfolio Management at a financial services firm with 1,001-5,000 employees
The customer support is great.
Director, Business Unit Servicenow at neverhack
 

Scalability Issues

Sentiment score
4.4
Dify is generally scalable, but larger workloads face challenges, especially self-hosted setups, with potential server issues noted.
Sentiment score
5.6
Private AI scalability varies, enhanced by strong infrastructure and frameworks, but relies on governance and hardware investments.
Rather than using a cloud-hosted platform, using a self-hosted platform means there can be scalability issues.
Automation Engineer at a tech services company with 1-10 employees
Dify's scalability is good and it handles growth or increased workloads effectively, depending upon the resources available.
Software Engineer at Futurescape Technologies
We did the performance testing for around 50 users, and Dify was complying properly.
AI Consultant at a tech vendor with 10,001+ employees
If I brought in an LLM and it starts phoning home to an IP address that's not within my organization, I would certainly hope my IT team would be monitoring that.
AI Strategy & Edge Computing Specialist at Kestrel Partners Group
There are very good frameworks available for scaling it up, such as DLRM.
Principal Software Developer at a consultancy with 11-50 employees
If you have a good partner that can provide the hardware and move fast on this, it should be a good point to start.
Head of Data & Analytics Department Senior Software Engineer at a tech services company with 501-1,000 employees
 

Stability Issues

Sentiment score
8.0
Dify is stable and scalable for production, with reliable self-hosting but AI relies on the models used.
Sentiment score
7.7
Users commend Private AI's stability, often surpassing foundation models, despite concerns about its investment needs for peak cloud performance.
It is not as stable as a cloud architecture.
Head of Data & Analytics Department Senior Software Engineer at a tech services company with 501-1,000 employees
Private AI is more stable than even the foundation models because I'm in charge.
AI Strategy & Edge Computing Specialist at Kestrel Partners Group
 

Room For Improvement

Dify needs more connectors, better templates, improved documentation, user interface updates, and enhanced workflow automation and community engagement features.
Private AI needs security, performance, user experience upgrades, better integration, and increased training for scalable, efficient deployment.
For EU customers, adding more documentation about how Dify processes the data when starting to use Dify would be really beneficial for companies in Europe to get started with Dify.
AI Consultant at AI Solution.dk
We currently use OpenAI Agents SDK, which requires you to build everything by code, but the observability is really good.
Automation Engineer at a tech services company with 1-10 employees
The only improvement would be if Dify provided an SMTP server that could be connected to automate Dify workflow management, as that would be a great option.
Software Engineer at Futurescape Technologies
The performance of models is affected by quantization type, MTU, token predictions, KV cache type, and cache size.
Principal Software Developer at a consultancy with 11-50 employees
Deploying a large language model of 70 billion parameters is not an easy task on an on-premise architecture because you have to provide many GPUs.
Head of Data & Analytics Department Senior Software Engineer at a tech services company with 501-1,000 employees
On the edge, I'm very limited on how much GPU memory I have compared to OpenAI that's got racks and racks of million-dollar servers with terabytes of space.
AI Strategy & Edge Computing Specialist at Kestrel Partners Group
 

Setup Cost

Enterprise buyers find Private AI pricing manageable but some view costs as high, especially those using token-based billing.
My experience with pricing, setup cost, and licensing is that it was free to use.
Automation Engineer at a tech services company with 1-10 employees
Dify is free to use and has a free license from GitHub under a Dify open-source license based on Apache 2.0.
Software Engineer at Futurescape Technologies
The experience with pricing is that it is quite reasonable.
AI Consultant at AI Solution.dk
Currently, I believe the cost is quite high.
Senior Project Analytics Consultant And Senior Manager Enterprise Portfolio Management at a financial services firm with 1,001-5,000 employees
We have software licenses for our software components.
Head of Data & Analytics Department Senior Software Engineer at a tech services company with 501-1,000 employees
 

Valuable Features

Dify offers agent orchestration, RAG capabilities, a simple UI, GDPR compliance, seamless integrations, and enhances workflows with easy AI model swaps.
Private AI offers secure data control, easy integration, compliance, and flexible architectures with enhanced functionality for efficient management.
Initially, we had about two weeks of time to implement the whole thing, but that was cut down to two days of time through using Dify.
Automation Engineer at a tech services company with 1-10 employees
Dify has positively impacted the organization because accuracy has been improved, and the time and complexity in flows that were manual are now automated.
Software Engineer at Futurescape Technologies
Dify stands out to me because it is compliant with GDPR, and it is 100% compliant with GDPR rules.
AI Consultant at AI Solution.dk
What makes the open-source models stand out for me compared to frontier models is that I could not afford running jobs 24/7 with proprietary solutions, which fundamentally changes my workflow.
Principal Software Developer at a consultancy with 11-50 employees
In terms of problem-solving velocity, we have sped up about 2,000 times before using this technology while also looking for specific types of activities to enhance operator growth.
Director, Business Unit Servicenow at neverhack
Security features impact my day-to-day work and my confidence in using the tool because I work for the insurance industry, which is a regulated industry that needs to comply with many guidelines and rules, and one of the most important is security and privacy.
Salesforce Architect at a consultancy with 51-200 employees
 

Categories and Ranking

Dify
Average Rating
8.4
Reviews Sentiment
5.3
Number of Reviews
9
Ranking in other categories
Low-Code Development Platforms (19th), AI Software Development (11th)
Private AI
Average Rating
7.6
Reviews Sentiment
5.8
Number of Reviews
11
Ranking in other categories
AI Professional Services (2nd)
 

Mindshare comparison

While both are Artificial Intelligence (AI) solutions, they serve different purposes. Dify is designed for Low-Code Development Platforms and holds a mindshare of 0.9%, up 0.0% compared to last year.
Private AI, on the other hand, focuses on AI Professional Services, holds 2.4% mindshare, down 2.9% since last year.
Low-Code Development Platforms Mindshare Distribution
ProductMindshare (%)
Dify0.9%
Microsoft Power Apps7.0%
OutSystems4.8%
Other87.3%
Low-Code Development Platforms
AI Professional Services Mindshare Distribution
ProductMindshare (%)
Private AI2.4%
Accenture AI services3.0%
Slalom2.7%
Other91.9%
AI Professional Services
 

Featured Reviews

Rusira Sathnindu - PeerSpot reviewer
Automation Engineer at a tech services company with 1-10 employees
Visual workflows have accelerated our agent POC while better UI and observability still need work
My personal experience with Dify's UI is that it is not my favorite, as it can be improved a little bit, and sometimes the UI feels a little bit buggy. I am not sure if that is because it was a self-hosted version. The documentation can also be improved a little bit more. I think not a lot of people are using Dify currently, so that is why the documentation is not very great. If the documentation was improved, that would also be a really good thing. Currently, Dify could improve by offering better observability like other platforms. We currently use OpenAI Agents SDK, which requires you to build everything by code, but the observability is really good. It has OpenAI Traces, and you can basically trace everything for a conversation. If Dify had that kind of tracing functionality, that would be great.
reviewer2867754 - PeerSpot reviewer
Principal Software Developer at a consultancy with 11-50 employees
Private workflows have transformed long‑running research while model setup still needs guidance
Regarding how Private AI can be improved, currently serving open weights models is complicated. There are many parameters that you have to adjust to make it run well. The ecosystem is maturing and becoming easier. Tools like Ollama allow running models with no friction, but with suboptimal performance. The speed of development is important as the ecosystem is advancing rapidly, and the tools and overlays need to catch up to make it easier for normal users. I have several computers of different kinds, such as a Mac Studio, a box in my house with NVIDIA GeForce cards like 3090, and a rented server with H100s or H200s. I do not know which quantization I should choose because quantization is complicated. The performance of models is affected by quantization type, MTU, token predictions, KV cache type, and cache size. Recipes for running models better would be appreciated. Some providers like Ansloth and G-Lang provide them, but they cover so much hardware that it is really hard to make a choice.
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Top Industries

By visitors reading reviews
Construction Company
15%
Comms Service Provider
15%
Manufacturing Company
11%
Computer Software Company
6%
Construction Company
27%
Insurance Company
14%
Comms Service Provider
12%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Large Enterprise4
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Dify?
The experience with pricing is that it is quite reasonable, and the setup cost depends on our usage, so I do not have any complaints regarding this.
What needs improvement with Dify?
I think Dify can be improved by adding a lot more connectors because the last time I checked Dify, which was about a month ago, it had fewer connectors as compared to other competitors such as Lang...
What is your primary use case for Dify?
My main use case for Dify is when we were building a logistic supply chain agent for a manufacturing company which manufactures steel, so for that, they needed interconnected agents who can coordin...
What needs improvement with Private AI?
I do not consider any improvements needed for Private AI.
What is your primary use case for Private AI?
My main use case for Private AI is for private data and coding. A specific example of how I use Private AI is analyzing data from the server. I do not have anything else to add about my main use ca...
What advice do you have for others considering Private AI?
My advice for others looking into using Private AI is to use it for research, so Private AI can advise others because that is now private. I would rate this product a 7 out of 10.
 

Comparisons

 

Overview

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