Software Alternatives, Accelerators & Startups

Parseur.com VS Keras

Compare Parseur.com VS Keras and see what are their differences

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Parseur.com logo Parseur.com

Automate text extraction from emails and PDFs by using our powerful email and document parser.

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
  • Parseur.com Landing page
    Landing page //
    2021-06-15

Parseur is a leading document processing software ranging from email parsing to PDF extraction. Use Parseur to automate text extraction from emails, PDFs, spreadsheets, attachments and documents and put your business on auto-pilot. Setup is easy as everything is point & click and intuitive. Send parsed data to thousands of applications in real time via our integrations with Google Sheets, Zapier, Microsoft Power Automate and Make or your custom application using webhooks.

Companies in finance, food delivery, real estate, e-commerce, marketing, logistics & delivery, travel, hospitality and more are saving thousands of work hours every month by automating their data entry process with Parseur.

  • Keras Landing page
    Landing page //
    2023-10-16

Parseur.com

$ Details
freemium $39.0 / Monthly (100 pages per month)
Platforms
Browser Web Google Chrome Cross Platform Firefox Safari
Release Date
2016 December

Keras

Website
keras.io
Pricing URL
-
$ Details
Platforms
-
Release Date
-

Parseur.com features and specs

  • Ease of Use
    Parseur offers an intuitive drag-and-drop interface, making it easy for users of any technical skill level to set up and customize data extraction templates.
  • Automation Capabilities
    The platform automates the process of extracting data from emails, simplifying workflows and reducing manual effort.
  • Integration Options
    Parseur supports multiple integrations with popular third-party applications like Zapier, Google Sheets, and various CRM systems, enabling seamless data transfer.
  • Support for Multiple File Types
    Parseur can handle various document formats including PDFs, Excel files, and plain text, expanding its usability across different use cases.
  • Accurate Data Extraction
    The platform uses machine learning algorithms to improve the accuracy of data extraction over time, reducing errors and improving data quality.
  • Scalability
    Designed to handle large volumes of data, whether you're processing a dozen emails or thousands, Parseur scales according to your needs.

Possible disadvantages of Parseur.com

  • Pricing
    The service can be expensive for small businesses or startups with limited budgets, especially if higher volumes of emails need to be processed.
  • Learning Curve
    Although the interface is user-friendly, some users may require time to fully understand all features and get the most out of the platform.
  • Limited Offline Capabilities
    Parseur requires an internet connection for most operations, which can be a drawback for users needing offline capabilities.
  • Customer Support
    Some users have reported delays in customer support response times, which can be problematic if immediate help is needed.
  • Template Management
    Managing multiple templates can become cumbersome, especially for businesses with complex and varied data extraction needs.
  • Feature Overload
    For some users, the plethora of features can feel overwhelming, making it easy to overlook or under-utilize certain functionalities.

Keras features and specs

  • User-Friendly
    Keras provides a simple and intuitive interface, making it easy for beginners to start building and training models without needing extensive experience in deep learning.
  • Modularity
    Keras follows a modular design, allowing users to easily plug in different neural network components, such as layers, activation functions, and optimizers, to create complex models.
  • Pre-trained Models
    Keras includes a wide range of pre-trained models and offers easy integration with transfer learning techniques, reducing the time required to achieve good results on new tasks.
  • Integration with TensorFlow
    As part of TensorFlowโ€™s ecosystem, Keras provides deep integration with TensorFlow functionalities, enabling users to leverage TensorFlow's powerful features and performance optimizations.
  • Extensive Documentation
    Keras has comprehensive and well-organized documentation, along with numerous tutorials and code examples, making it easier for developers to learn and use the framework.
  • Community Support
    Keras benefits from a large and active community, which provides support through forums, GitHub, and specialized user groups, facilitating the resolution of issues and sharing of best practices.

Possible disadvantages of Keras

  • Performance Limitations
    Due to its high-level abstraction, Keras may incur performance overheads, making it less suitable for scenarios requiring extremely fast execution and low-level optimizations.
  • Limited Low-Level Control
    The simplicity and abstraction of Keras can be a downside for advanced users who need fine-grained control over model components and custom operations, which may require them to resort to lower-level frameworks.
  • Scalability Issues
    In some complex applications and large-scale deployments, Keras might face scalability challenges, where more specialized or low-level frameworks could handle such tasks more efficiently.
  • Dependency on TensorFlow
    While the integration with TensorFlow is generally an advantage, it also means that the performance and features of Keras are closely tied to the development and updates of TensorFlow.
  • Lagging Behind Latest Research
    Keras, being a user-friendly high-level API, might not always incorporate the latest cutting-edge research advancements in deep learning as quickly as more research-oriented frameworks.

Analysis of Parseur.com

Overall verdict

  • Parseur.com is generally well-regarded in the industry for its user-friendly approach and robust features, making it a worthwhile tool for businesses in need of parsing solutions.

Why this product is good

  • Parseur.com is considered a good option because it provides a reliable and efficient email parsing solution that automates data extraction from emails, PDFs, spreadsheets, and other documents. It offers an easy-to-use interface, powerful workflows, and integration capabilities with various applications, making it suitable for businesses looking to streamline data processing tasks.

Recommended for

  • Businesses needing to automate data extraction from documents
  • Companies looking to integrate data parsing with other applications
  • Users seeking a no-code or low-code data processing tool
  • Organizations wanting to improve efficiency in data handling and management

Analysis of Keras

Overall verdict

  • Keras is a solid choice for deep learning projects, offering simplicity and flexibility without sacrificing performance. It is well-suited for educational purposes, research, and even deploying models in production environments.

Why this product is good

  • Keras is widely regarded as a good deep learning library because it provides a user-friendly API that allows for easy and fast prototyping of neural networks. It is built on top of other libraries like TensorFlow, making it robust and efficient for both beginners and experienced developers. Its modularity, extensibility, and compatibility with other tools and libraries make it a popular choice for developing deep learning models.

Recommended for

  • Beginners who are new to deep learning
  • Researchers looking for an easy-to-use platform for prototyping models
  • Developers working on projects that require quick experimentation and development
  • Individuals and companies deploying models into production environments

Parseur.com videos

Meet Parseur, a powerful tool to extract text from emails and PDFs

Keras videos

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Category Popularity

0-100% (relative to Parseur.com and Keras)
Data Extraction
100 100%
0% 0
Data Science And Machine Learning
AI
100 100%
0% 0
OCR
50 50%
50% 50

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Parseur.com and Keras

Parseur.com Reviews

  1. Parsing PDF at ease

    When dealing with entities that send lots of data in an unstructured way because they think a PDF is the end of their digitalization process, Parseur is a great tool to automate reading this PDF and converting its data into structured json and then from their you can send it to your endpoint.

  2. Thomas Brunkard
    ยท Head of Marketing at Solution Centre ยท
    Powerful Solution with Excellent Support

    Email may probably never die but that doesn't mean that business processes should be slowed or halted. Parseur enables us to create a lot more efficiencies by handling email data as though it was keyed in by a customer agent.

    There are other services that do this but for the low cost and the ease of use, this service is the best.

    For those of us working in the European Union, Parseur was also easy to assess and approve for GDPR requirements.

    The support for post processing is very powerful and with a extensive export options, it is very easy to get data into the right funnel.

    ๐Ÿ Competitors: Mailparser, Parserr
    ๐Ÿ‘ Pros:    Quickly compliant with gdpr|Microsoft power automate ready|Its flexible and easy to use|Outstanding customer support

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by Franรงois Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...

Social recommendations and mentions

Based on our record, Keras should be more popular than Parseur.com. It has been mentiond 35 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Parseur.com mentions (12)

  • Is it Possible to have info from text messages/emails auto added or removed from an Excel sheet as they come in?
    You can get an account with https://parseur.com/ and then a number with OpenPhone, and Zappier. Those 3 will let you do what you want (easily). Source: over 3 years ago
  • Building an email parser with ChatGPT-4 and Laravel
    Iโ€™m sure this is super cool, but have you considered https://parseur.com itโ€™s built for stuff like this. Source: over 3 years ago
  • Using Power Automate To Parse Email and Extract Information From The Body
    For more complex layouts, or if you have to deal with several layouts, it may be better to use third party document extraction tool that connects to like Parseur. Source: over 3 years ago
  • Email, PDF, to Sales order? Automate Sales Order Entry
    You could use a document parser tool, like Parseur to better automate the process. Source: almost 4 years ago
  • CEO looking for a solution
    And if you ever are in need of an intelligent document processing software, have a look at Parseur.com (of which I'm the co-founder, sorry for the shameless plug ;-)). Source: over 4 years ago
View more

Keras mentions (35)

  • Top Programming Languages for AI Development in 2025
    The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / about 1 year ago
  • Top 8 OpenSource Tools for AI Startups
    If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and runningโ€”an essential part of the startup hustle. - Source: dev.to / over 1 year ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / almost 2 years ago
  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / about 2 years ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Parseur.com and Keras, you can also consider the following products

DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ€™ platform makes it straightforward and fast to create highly accurate Deep Learning models.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Parsio.io - No-code email & PDF parser

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.