Software Alternatives, Accelerators & Startups

ProcessMaker VS Keras

Compare ProcessMaker VS Keras and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

ProcessMaker logo ProcessMaker

ProcessMaker is a top-notch Low Code BPM platform used by dozens of businesses worldwide to design and deploy complex processes.

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.
  • ProcessMaker Landing page
    Landing page //
    2023-07-14
  • Keras Landing page
    Landing page //
    2023-10-16

ProcessMaker features and specs

  • User-Friendly Interface
    ProcessMaker offers a drag-and-drop interface that simplifies the design of workflows and business processes for users with minimal coding expertise.
  • Rapid Deployment
    The low-code nature of ProcessMaker allows for faster implementation of business processes, enabling quicker transformation and adaptation to business needs.
  • Cost-Effective
    By allowing users to develop applications with minimal coding, ProcessMaker can reduce the need for extensive IT resources, leading to cost savings.
  • Integration Capabilities
    ProcessMaker supports integration with various third-party applications, which helps create seamless workflows across different systems.
  • Scalability
    ProcessMaker's cloud-based architecture supports scalability, allowing businesses to grow without major changes to their process management systems.
  • Extensive Integration Capabilities
    ProcessMaker supports integration with a wide array of third-party applications and services, including ERP systems, CRM systems, and web services. This allows for seamless data flow between different systems.
  • Agentic AI Workflows
    ProcessMaker supports Agentic AI, allowing users to create autonomous agents that can execute workflows, make decisions, and interact with systemsโ€”without human intervention.
  • Process Documentation
    Ensure your workflows are properly documented with little effort. AI documentation will create explanations for your entire process including all of its steps and assets. Or start with the documentation: explain your process first in your own words and generate functional workflow automations from scratch.
  • Robust Reporting and Analytics
    The platform offers extensive reporting and analytics capabilities. Users can generate various reports to track the performance of workflows and gain insights into operational bottlenecks, improving overall efficiency.

Possible disadvantages of ProcessMaker

  • Customization Limitations
    While ProcessMaker is powerful, there may be some advanced customization needs that require additional coding, which could be a limitation for complex processes.
  • Learning Curve
    For users who are not familiar with BPM or low-code platforms, there can be an initial learning curve that may require training.
  • Performance Issues
    Some users have reported performance issues, particularly when dealing with very large workflows or significant data loads.
  • Dependency on Vendor
    Reliance on ProcessMaker for ongoing updates and support could be a concern if the vendor's priorities change or if they discontinue support.
  • Limited Offline Functionality
    Since ProcessMaker is cloud-based, its functionality is limited when offline, which might be a drawback for some mobile or remote scenarios.
  • Cost of Premium Features
    While the open-source version is free, many advanced features and capabilities are only available in the paid enterprise version. Organizations may incur significant costs if they require these premium features.
  • Scalability Issues
    Some users have reported performance issues and scalability limitations when handling very large or complex workflows. This can be a concern for large enterprises with extensive process automation needs.
  • Limited Customization in UI
    Although ProcessMaker is highly customizable in terms of workflow logic, the customization options for the user interface are somewhat limited compared to other BPM tools. This can be limiting for organizations wanting a highly tailored user experience.
  • Dependency on Third-Party Plugins
    The tool often relies on third-party plugins to extend its functionality. While this makes it versatile, it also introduces potential dependency issues and can complicate the upgrade and maintenance processes.

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 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

ProcessMaker videos

ProcessMaker's Transfer Credit Evaluation

More videos:

  • Demo - Process Intelligence Explainer
  • Demo - ProcessMaker Platform Explainer

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 ProcessMaker and Keras)
Project Management
100 100%
0% 0
Data Science And Machine Learning
Business & Commerce
100 100%
0% 0
OCR
0 0%
100% 100

User comments

Share your experience with using ProcessMaker and Keras. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

ProcessMaker Reviews

7 Best Business Process Management Tools (2023)
ProcessMaker is a flexible and intuitive software suite that allows you to create, manage, and deploy complex workflows using visual design, and an integrated UI for management, simulation, and testing.
Top 7 Workflow Software (2020 Reviews)
ProcessMaker is an open-source workflow automation software thatโ€™s best suited for large companies. Its low-code business process management platform lets users design and automate workflows quickly.
Source: clickup.com
10 Best Open Source BPM Tools
ProcessMaker is a software that allows you to model your business processes. You access a graphical interface on which you can drag the different constituent elements of your workflows.
20 Free Open Source BPM Software for Businesses in 2021
ProcessMaker Workflow BPM is one of the top open-source BPM software solutions that helps in creating a navigable framework of business processes. It is cloud-based and can be accessed from all popular devices and browsers. The best think is that it can be used by businesses of all the sizes and requirements
Top 15 Workflow Management Software Solutions
ProcessMaker is an easy to use and cost effective open source business process management (BPM) and workflow software tool. It is lightweight, very efficient, and has a low overhead. Numerous business analysts and subject matter experts use ProcessMaker as their workflow software solution because it enables them to communicate with their technical teams effectively and...

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 seems to be more popular. 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.

ProcessMaker mentions (0)

We have not tracked any mentions of ProcessMaker yet. Tracking of ProcessMaker recommendations started around Jul 2021.

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 / over 2 years ago
View more

What are some alternatives?

When comparing ProcessMaker and Keras, you can also consider the following products

Kissflow - Kissflow is a workflow tool & business process workflow management software to automate your workflow process. Rated #1 cloud workflow software in Google Apps Marketplace.

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.

ProntoForms - ProntoForms is a mobile business solutions application, converting paper forms onto any tablet or mobile device.

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

Now Platform - Get native platform intelligence, so you can predict, prioritize, and proactively manage the work that matters most with the NOW Platform from ServiceNow.

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