1.What is the difference between your product and SOCRATES, which is sold here on APPSUMO?
2.I have 15 PDFs I want to chat with, totaling 5800 pages. Does your app support this amount of data? For each question, I want the source citation to verify if it is accurate. For example, SOCRATES sometimes hallucinates, so at least I want the citation to have a link to check.
3.Can the chat be exported as a PDF? 4.Can the chat be shared?
A: 1. I answered this question before, so I will just copy what i said back then: A: It's always good to explore the options out there. While we’re aware of many players in the space (you can find a comparison section on our website), each tool brings its own strengths and limitations. I never heard about Socrates until today. I just did try Socrates with a book for comparison. In my experience, it is a bit slower and lacks some of the capabilities we offer—such as API access, customizable AI agents, and a broader selection of models and settings. The user experience also feels quite different. That said, the best way to decide is to try both and see which one fits your workflow better. We’re confident that docAnalyzer’s flexibility, speed, and feature set stand out, especially for professional or high-volume use. Yes — but it’s important to understand how large language models (LLMs) work so you set realistic expectations.
2) A dataset of 5,800 pages is roughly 4 million tokens (though the exact number depends on text density, language, formatting, etc.).
Currently, even the best LLMs have a context window of around 1–2 million tokens, meaning you can’t simply feed the entire dataset into the model in a single prompt.
You also need to factor in: ✅ How long you want the answer/output to be (because that also consumes part of the context window) ✅ The fact that as you push toward the maximum context window, accuracy can drop and the risk of hallucinations increases
We cover all this in more detail here: FAQ – Working with Large Datasets: https://docanalyzer.ai/faq/chat/large-dataset#large-dataset
Why is DocAnalyzer a great fit for large datasets? ✅ You can fine-tune the context window budget ✅ You get access to a wide range of LLMs ✅ We provide high-quality embedding search, so you can work efficiently even with massive documents
My answer was YES. It's indeed possible to chat with 15 PDFs at once. The system will analyze your question and send relevant extracts to the LLM. Some type of question won't work well, for these you can use our Individual AI agent that with one prompt ask the same question for each PDF.
Our OCR and data extraction have delivered excellent results across a wide range of use cases. Accuracy often depends on the document type, structure, and the AI model selected—docAnalyzer.ai gives you access to several top-tier models for flexibility.
We encourage you to try a comparison using your own documents. You can upload samples on our free plan to see how our system performs against others like Koncile and Mindee.
Thanks for your reply. Actually I've tried OCR within DocAnalyzer for big scanned documents and it works quite fine. However, it is disappointing that, after OCR is applied using credits (costly), it is not possible yet to download the OCR converted document with added text layer (the downloaded file is still the original one without text layer). Can you please add this option to your to-do list?
Thank you for the feedback and for testing our OCR feature on large scanned documents — we're glad to hear it’s working well for you! You're absolutely right about the download limitation, and we understand how valuable it would be to retrieve the OCR-processed file with the added text layer. The good news: this is already on our roadmap and planned for a future update.
Q: Improvements for health research?
Hi there,
I tried DocAnalyzer last year, but neeed to refund due to lack of accuracy and depth by that time.
Thinking of trying again... Have there been major improvements since then?
Which models are now used?
Is it now solid for multiple cross-document (some of them are realy large ones) analysis in health/scientific research?
A: Thanks for checking back in—and yes, there have been a sea of changes since last year!
We’ve significantly improved our platform for research-heavy use cases like scientific analysis. Here are some key updates:
Model selection: We now support a wide range of top-tier models including GPT-4.1, Claude 3.7 Sonnet, and Gemini 2.5. Check our model page: https://docanalyzer.ai/models
Multi-document analysis: We’ve enhanced performance for large and cross-document analysis, including new AI agent tools like Individual, Page Group, and Filter—perfect for deep dives across large datasets.
Team features & roadmap: A team plan is now available, and you can check our public roadmap to see the full history of updates. We'd love to have you give it another try—and this time, we're confident you'll notice the difference.
Q: Very interesting
1.What is the difference between your product and SOCRATES, which is sold here on APPSUMO?
2.I have 15 PDFs I want to chat with, totaling 5800 pages. Does your app support this amount of data? For each question, I want the source citation to verify if it is accurate. For example, SOCRATES sometimes hallucinates, so at least I want the citation to have a link to check.
3.Can the chat be exported as a PDF?
4.Can the chat be shared?
Christophe_docAnalyzer.ai
May 28, 2025A: 1. I answered this question before, so I will just copy what i said back then:
A: It's always good to explore the options out there. While we’re aware of many players in the space (you can find a comparison section on our website), each tool brings its own strengths and limitations. I never heard about Socrates until today.
I just did try Socrates with a book for comparison. In my experience, it is a bit slower and lacks some of the capabilities we offer—such as API access, customizable AI agents, and a broader selection of models and settings. The user experience also feels quite different.
That said, the best way to decide is to try both and see which one fits your workflow better. We’re confident that docAnalyzer’s flexibility, speed, and feature set stand out, especially for professional or high-volume use.
Yes — but it’s important to understand how large language models (LLMs) work so you set realistic expectations.
2) A dataset of 5,800 pages is roughly 4 million tokens (though the exact number depends on text density, language, formatting, etc.).
Currently, even the best LLMs have a context window of around 1–2 million tokens, meaning you can’t simply feed the entire dataset into the model in a single prompt.
You also need to factor in:
✅ How long you want the answer/output to be (because that also consumes part of the context window)
✅ The fact that as you push toward the maximum context window, accuracy can drop and the risk of hallucinations increases
We cover all this in more detail here: FAQ – Working with Large Datasets: https://docanalyzer.ai/faq/chat/large-dataset#large-dataset
Why is DocAnalyzer a great fit for large datasets?
✅ You can fine-tune the context window budget
✅ You get access to a wide range of LLMs
✅ We provide high-quality embedding search, so you can work efficiently even with massive documents
3. We don't have yet this feature
4.Yes.
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Please confirm for me that I can chat and consult with those 15 PDFs at the same time.
Hello, so there is no way to search all 15 PDFs I have at once; would I then have to search them one by one? Some PDFs I have contain 600 pages.
My answer was YES. It's indeed possible to chat with 15 PDFs at once. The system will analyze your question and send relevant extracts to the LLM. Some type of question won't work well, for these you can use our Individual AI agent that with one prompt ask the same question for each PDF.
thanks
Q: Can you also add reply in Tranditional Chinese too?
Could you please add Traditional Chinese in Preferred language answer output ?
Christophe_docAnalyzer.ai
May 25, 2025A: It's been added (will be deployed in the next few days).
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Q: Credits
Hi,
Are the API credits for each account or the entire team 4,000?
Christophe_docAnalyzer.ai
May 24, 2025A: AppSumo tier 3 credits (4000) are for the entire team.
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Q: How DocAnalyzer compares with Koncile and Mindee in regards of docs recognition accuracy and data extraction ?
Christophe_docAnalyzer.ai
May 11, 2025A: Great question!
Our OCR and data extraction have delivered excellent results across a wide range of use cases. Accuracy often depends on the document type, structure, and the AI model selected—docAnalyzer.ai gives you access to several top-tier models for flexibility.
We encourage you to try a comparison using your own documents. You can upload samples on our free plan to see how our system performs against others like Koncile and Mindee.
Share docAnalyzer.ai
Verified purchaser
Thanks for your reply. Actually I've tried OCR within DocAnalyzer for big scanned documents and it works quite fine. However, it is disappointing that, after OCR is applied using credits (costly), it is not possible yet to download the OCR converted document with added text layer (the downloaded file is still the original one without text layer). Can you please add this option to your to-do list?
Thank you for the feedback and for testing our OCR feature on large scanned documents — we're glad to hear it’s working well for you!
You're absolutely right about the download limitation, and we understand how valuable it would be to retrieve the OCR-processed file with the added text layer. The good news: this is already on our roadmap and planned for a future update.
Q: Improvements for health research?
Hi there,
I tried DocAnalyzer last year, but neeed to refund due to lack of accuracy and depth by that time.
Thinking of trying again... Have there been major improvements since then?
Which models are now used?
Is it now solid for multiple cross-document (some of them are realy large ones) analysis in health/scientific research?
Thanks!
Christophe_docAnalyzer.ai
May 6, 2025A: Thanks for checking back in—and yes, there have been a sea of changes since last year!
We’ve significantly improved our platform for research-heavy use cases like scientific analysis. Here are some key updates:
Model selection: We now support a wide range of top-tier models including GPT-4.1, Claude 3.7 Sonnet, and Gemini 2.5. Check our model page: https://docanalyzer.ai/models
Multi-document analysis: We’ve enhanced performance for large and cross-document analysis, including new AI agent tools like Individual, Page Group, and Filter—perfect for deep dives across large datasets.
Team features & roadmap: A team plan is now available, and you can check our public roadmap to see the full history of updates. We'd love to have you give it another try—and this time, we're confident you'll notice the difference.
Share docAnalyzer.ai