Artificial intelligence technology is used in the technical process by which a machine decides using logic. The development of talking chatbots, self-driving cars, and recommendation engines clearly illustrates how AI is utilized in this research worldwide. It touches all aspects of life and is one of the most active fields of technological research. By using cutting-edge technology like artificial intelligence, machine learning, and many others, AI companies are expanding exponentially all over the world. These AI companies have a significant demand for open-source AI software to assist in training models using algorithms and adequate, relevant data. Developers and AI businesses can create intelligent applications using a variety of AI software. AI businesses employ open-source AI software to automate repetitive operations, develop predictive analytics, make smart decisions, build conversational user interfaces, and many other uses. In order to increase productivity, here you can examine some of the best ten open-source AI software to download and use:

1. TensorFlow

One of the most popular works of open-source AI software, TensorFlow, is regarded as the all open-source machine platform. The open-source library helps in AI businesses’ machine learning model training process. It advances the state-of-the-art when delivering machine learning-based applications and offers a vast ecosystem of tools and libraries.

By creative predictive modelling applications using this software, you may utilize the potential of data in your company. Models are built using this software using data flow graphs. This software can be applied to perception, understanding, prediction, creation, and classification.

Time-series data, text-based applications, image identification, video detection, and voice/sound recognition are where you will find the main applications for this software. The areas of finance, accounting, and enterprise planning are where TensorFlow’s time series algorithms are most frequently applied.

Key features:

  • The ability to support several languages, including JavaScript, which is uncommon in the open-source area of artificial intelligence 
  • The use of intuitive high-level APIs, such as Keras, to create and train ML models quickly
  • Platform-neutral ML production is available on-premises, in the cloud, through a browser, or locally on a device.
  • TensorFlow Lite for embedded, IoT, and mobile applications
  • Cross-compatibility of AI/ML models you have trained on several TensorFlow iterations
  • A wide range of applications, such as conversational AI, object classification, and predictive analysis

2. PyTorch

As an open-source framework for artificial intelligence and machine learning, PyTorch is one of the best AI software available. It speeds up the transition from research prototyping to implementation in the marketplace. This PyTorch has a vast scope of features and capabilities. It provides modes that are prepared for production, distributed training, performance optimization, a strong ecosystem, and cloud support.

Key features

  • A TorchServe-powered setup that is ready for production that allows for speedy model deployment
  • A distributed backend architecture that enables distributed training and performance optimization o Computer vision and natural language processing algorithms 
  • Support for all major public clouds for flexible development 
  • End-to-end Python to iOS/Android workflow for developing mobile apps 
  • Native exports from Open Neural Network Exchange (ONNX)

3. OpenCV

OpenCV offers vision and AI consulting services as one of the top platforms for artificial intelligence. AI companies use this open-source AI software because artificial intelligence algorithms can recognize and track things with detection models as small as 600 Kb. It can be applied to a variety of tasks, including workout analysis and AR clothes fitting, among others.

Key features

  • Proven applications for various use cases, such as motion tracking, object detection, human-computer interfaces, facial recognition, and more.
  • A machine learning library that includes, among other things, the k-nearest neighbour method, deep neural networks (DNN), random forests, and decision trees for learning
  • Compatibility with every desktop ecosystem, including Android, iOS, Maemo, and BlackBerry 10.
  • Pay-for-performance classes in deep understanding, use cases, and computer vision
  • Mainly created in C++, with wrappers in Python, Java, etc.
  • A supplier of spatial imaging cameras

4. OpenNN 

A basis for the study and creation of neural network algorithms and applications is provided by the well-liked and efficient AI software OpenNN. With numerous goal functions and training in artificial intelligence and neural network algorithms, it is a thorough implementation of the multilayer perceptron neural network in the C++ programming language.

key features of OpenNN include:

  • software library built with C++
  • Regression modelling for ML outputs
  • Using data classification to identify particular patterns
  • Using historical data to inform predictions
  • mapping the associations between two correlated variables
  • a tool for neural designers to simplify the creation of neural networks

5. IBM Watson

IBM Watson is an open-source, free AI software that gives businesses the power to calculate disruptions, accelerate research and development, and enhance interactions. Many companies use this software to analyze their data, collect ideas and information, and estimate their future performance easily. Organizations may make better decisions by utilizing IBM’s cloud-based platform.

The IoT, consumer interaction, education, healthcare, energy, finance, work, and transportation sectors are just a few industries for which it is intended for businesses. Enterprises can find new opportunities and keep up with potential rules and hazards by utilizing cutting-edge AI and machine learning. You can boost your productivity by using this software.


  • It is compatible with the current tools and supports distributed computing.
  • It offers an API for creating applications.
  • It is also capable of learning from small data.

6. Rasa Open Source

Rasa is one of the most well-liked open-source AI tools for creating conversational user interfaces. Although the business primarily derives revenue from its commercial solution, it also offers a powerful open-source edition and a unique set of tools for expanding AI support. Rasa provides a library of pre-built TensorFlow models that you may use to create your machine learning models. Rasa Enterprise adds SSO-based security, service level agreements, and devoted Support to the open-source platform.

 Key features: 

  • ML-powered dialogue management to control the assistant’s conversation flows depending on the context
  • Natural language understanding to turn messages into structured data and assess intent
  • Complete view into the AI training pipeline, model architecture, and underlying technology 
  • Built-in integration for more than ten common communications channels 
  • Strong Support from the community, with over 10,000 forum participants and an optional Rasa X toolkit for testing, improvements, and new releases

7. Acumos AI

Acumos was established in 2019, making it a newcomer to the open-source AI software market, but it is supported by two major players in the space: AT&T and TechMahindra. By making AI available for commercial deployments, the two businesses hoped to buck the trend of tech greats like Microsoft, Google, and Apple driving open-source innovations. In order to facilitate the integration of various frameworks and the creation of cloud-based AI apps, they did this by introducing Acumos AI, a design studio based on Linux.

 Key features: 

  • Various AI libraries can be found and used in the Acumos marketplace.
  • A community to create market-based solutions. 
  • Onboarding assistance to promote interoperability. 
  • A graphical interface to manage AI models in advance of a runtime environment.
  • API connectivity and microservices tools 
  • Support for Dockerization to run AI within a container

8. Apache Mahout

AI companies frequently use Apache Mahout to create a scalable, effective machine learning and artificial intelligence systems. It is a distributed linear algebra framework that supports various distributed backends, has modular native solvers for CPU/GPU/CUDA acceleration, and has mathematically expressive Scala DSL.

Key features:

  • Supports a user community 
  • focuses on real-world issues
  • Extensible programming framework, 
  • scalable algorithms, 
  • clustering & classification, 
  • adequate documentation,
  • multi-languages, process/workflow automation,
  • speech recognition, adaptive and chatbot, digital assistants, multi-languages, etc.

9. Torch.AI

AI finds valuable information in data and boosts human and robot productivity. With the help of artificial intelligence, Torch.AI, an open-source AI software, helps people reach their full potential. AI businesses utilize this software because it offers the fastest data processing platform available, which speeds up processing times and lowers operational expenses.

This free AI software app comes with a wide ecosystem of community-driven packages for image, video, and audio processing, parallel computing, signal processing, networking, machine learning, computer vision, and other related fields.

Key features:

  • Chatbot & speech recognition 
  • Adaptive & Digital Assistants
  • N-dimensional array
  • Machine learning
  • GPU support
  • Routines for indexing, slicing, transposing
  • Fixed with ports to iOS and Android backends
  • Neural network
  • Energy-based models
  • Predictive Analytics

10. Weka

Weka is a collection of machine learning methods for solving practical data mining issues. It was created in Java and worked with nearly every platform. You can invoke the algorithms directly from your own Java code or apply them directly to a dataset.


  • machine learning
  • data mining
  • clustering
  • preprocessing
  • classification
  • regression
  • experiments
  • association rules
  • attribute selection
  • workflow
  • visualization

Bottom Line

AI is not only useful for consumer applications, but it also provides a considerable advantage for businesses and economies by promoting productivity development. Numerous practical uses of AI, like facial recognition, language translation, and personal assistants, are influenced by it. You can use it for your business requirements. Your particular software development requirements will ultimately determine your chosen open-source AI technology. The above listed are the top ten open-source AI software.