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Deeplearning4j VS KeptPDF

Compare Deeplearning4j VS KeptPDF and see what are their differences

Deeplearning4j

Deeplearning4j is an open-source, distributed deep-learning library written for Java and Scala.

Rating
0 reviews
Alternatives Is it good?
KeptPDF

Redact, edit, OCR, and sign PDFs entirely in your browser. The file never leaves your device. Free, no account needed.

Rating
0 reviews
Pricing
Freemium $29 / Monthly (Pro, 1 user)
Alternatives Is it good?
Tempreon
A personal memory layer for your AI tools, connected over MCP. sponsored

Which is more popular?

Based on our record, Deeplearning4j seems to be more popular. It has been mentioned 6 times since March 2021.

social mentions
6 vs 0
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
44 vs 20

Base details

Website, pricing, platforms and company facts side by side.

Deeplearning4j
KeptPDF
Website deeplearning4j.org keptpdf.com
Pricing —
Freemium $29 / Monthly (Pro, 1 user) Official pricing
Company — Startup from the United States · 2026
Listed in
OCR Machine Learning Image Analysis Deep Learning +1
PDF Tools Pdf Redaction OCR PDF Editor PDF Security & Privacy PDF Readers And Editors AI Tools +5

About Deeplearning4j and KeptPDF

In their own words, as submitted to SaaSHub.

Deeplearning4j
KeptPDF

No description of Deeplearning4j yet.

KeptPDF is a PDF toolkit that runs entirely in your browser. Nothing uploads: every tool runs on your own device, so the document never touches a server. What it does: Redaction that auto-detects names, SSNs, phone numbers, addresses, and dates, then removes the underlying text instead of drawing...

Read more about KeptPDF

Features and specs

What each product offers, as listed by its team.

Deeplearning4j 5 features
KeptPDF 5 features
  • Java Integration
    Deeplearning4j is written for Java, making it easy to integrate with existing Java applications. This is a significant advantage for businesses running Java systems.
  • Scalability
    It is designed for scalability and can be used in distributed environments. This is ideal for handling large-scale datasets and heavy computational tasks.
  • Commercial Support
    Deeplearning4j offers professional support through commercial entities, which can be beneficial for enterprises needing reliable assistance and maintenance.
  • Compatibility with Hardware
    It provides compatibility with GPUs and various processing environments, allowing efficient training of deep networks.
  • Ecosystem
    Deeplearning4j is part of a larger ecosystem, including tools like DataVec for data preprocessing and ND4J for numerical computing, providing a comprehensive suite for machine learning tasks.

Possible disadvantages

  • Learning Curve
    It can have a steep learning curve, especially for developers not already familiar with the Java programming language or deep learning concepts.
  • Community Size
    The community and available resources are not as extensive as those for other deep learning libraries like TensorFlow or PyTorch. This might limit access to free and diverse community support.
  • Less Popularity
    Compared to more popular frameworks like TensorFlow or PyTorch, Deeplearning4j is less commonly used, which may affect library updates and third-party tool integrations.
  • Performance
    In some use cases, performance can lag behind other optimized frameworks that extensively use C++ and CUDA, particularly for specific models or complex operations.
  • Simple PDF Editing
    KeptPDF offers straightforward tools for editing, merging, splitting, and converting PDF files, making it accessible for users who need quick document management without a steep learning curve.
  • Web-Based Accessibility
    Being a web-based tool, KeptPDF can be accessed from any device with an internet connection, eliminating the need for software installation and allowing use across different operating systems.
  • Multiple File Format Support
    The platform supports conversion between PDF and various other file formats, offering flexibility for users who work with documents in different formats.
  • No Installation Required
    Since it operates in a browser, users can save storage space on their devices and avoid compatibility issues that sometimes arise with desktop software installations.
  • Quick Processing
    KeptPDF is designed to process PDF tasks efficiently, allowing users to complete common document tasks like compression or conversion in a relatively short amount of time.

Videos

Walkthroughs and reviews on video.

Deeplearning4j 1 video + Add
KeptPDF 0 videos + Add

Deep Learning with DeepLearning4J and Spring Boot - Artur Garcia & Dimas Cabré @ Spring I/O 2017

No KeptPDF videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Deeplearning4j
KeptPDF
100% 100%
Data Science And Machine Learning
0% 0%
0% 0%
PDF Tools
100% 100%
100% 100%
OCR
0% 0%
0% 0%
PDF
100% 100%

Questions & Answers

As answered by people managing Deeplearning4j and KeptPDF.

What makes your product unique?

KeptPDF's answer:

KeptPDF runs entirely in your browser. Your file, and the text inside it, never leaves your device. Not to an AI, not even to us. You can open your browser's network tab and watch: the document bytes never go out.

Most online PDF tools upload your file to a server first, and some "AI redaction" services quietly send your document text to a third-party model. That is the exact risk people are trying to avoid when they redact something.

KeptPDF also does true redaction. The text is removed from the file, not covered with a black box you can copy out later. Every redaction produces a verification certificate you can share with the file.

Why should a person choose your product over its competitors?

KeptPDF's answer:

Three reasons.

Privacy you can verify, not just a promise. Processing happens locally in the browser, so there is no upload step to trust. We do send anonymous usage counts for quota, and we say so plainly, but never your document.

Real redaction with proof. Removed text is permanently gone, and you get a certificate showing the file was checked for leftover extractable text. Automated detection cannot catch everything, so a final human review is still your job, and the tool says that too.

It works on a phone. Most PDF suites assume a desktop. KeptPDF was built and used on a phone first, so redacting a document while you are standing in a hallway actually works.

How would you describe the primary audience of your product?

KeptPDF's answer:

Anyone who has to hand a document to someone else and needs the sensitive parts gone first.

In practice that is solo attorneys and small law firms, accountants and tax preparers, healthcare and records staff handling requests, HR teams, and individuals dealing with their own medical, legal, or financial paperwork.

The common thread is not an industry. It is a person who cannot upload a confidential file to a random website, and who does not have an enterprise IT budget to solve it.

What's the story behind your product?

KeptPDF's answer:

A family member got seriously ill. We spent most days at the hospital, and straight answers were hard to come by, so we leaned on AI tools to make sense of the records, notes, and lab results.

But you cannot paste a medical record into an AI chat. You have to strip the names, the ID numbers, the diagnoses first. And almost every tool we found either wanted to upload the whole file to a server, or "auto-redacted" by sending the document text to an online AI. That was the exact thing we were trying to avoid.

Most of this was happening on a phone, at a bedside. So I built the tool I needed: redaction that runs on the device, works on mobile, and never sends the file anywhere. That turned into KeptPDF, which is now a full PDF suite with over 20 tools, all local-first.

Which are the primary technologies used for building your product?

KeptPDF's answer:

The app is plain JavaScript with no front-end framework, which keeps it fast and keeps the code auditable.

PDF work happens in the browser using pdf.js for rendering and pdf-lib for writing. Text recognition uses Tesseract running as WebAssembly. Password and encryption handling uses a WebAssembly build of qpdf. It is a Progressive Web App, so it installs and works offline.

The thin server side is Node on Vercel, with Postgres for accounts, Stripe for billing, and Resend for email. None of those ever see a document.

Who are some of the biggest customers of your product?

KeptPDF's answer:

KeptPDF is early and independent, and we do not publish customer names. The product is privacy-first by design: we never see your documents, and we do not track who our users are or what they work on. Publishing a client list would sit badly next to that.

The user base today is mostly solo attorneys, small firms, accountants, and individuals handling their own records.

User comments

Share your experience with using Deeplearning4j and KeptPDF. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Deeplearning4j 6 mentions
KeptPDF 0 mentions
  • DeepLearning4j Blockchain Integration: Convergence of AI, Blockchain, and Open Source Funding
    This integration is not only a technical marvel but also a case study in how open source funding and a transparent business model powered by blockchain are fostering collaboration among developers, academics, and institutional investors.... - Source: dev.to / over 1 year ago
  • DeepLearning4j Blockchain Integration: Merging AI and Blockchain for a Transparent Future
    DeepLearning4j Blockchain Integration is more than just a convergence of technologies; it’s a paradigm shift in how AI projects are developed, funded, and maintained. By utilizing the robust framework of DL4J, enhanced with secure... - Source: dev.to / over 1 year ago
  • Machine Learning in Kotlin (Question)
    While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features. Source: about 5 years ago

View more

Tracking KeptPDF since Aug 2026.

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