7 Best Artificial Intelligence Software Development Tools in 2023

Artificial Intelligence is no more a fantasy, it’s the utter reality of the modern world. Businesses leverage Artificial Intelligence (AI) in multiple ways to streamline their processes, implement automation, and make better decisions through data analysis.

The use of artificial intelligence is rising at a never-ending speed. Indeed, the annual growth of AI is expected to be 37.3% from the year 2023 to the year 2030. These stats showcase the popularity of AI. 

Artificial Intelligence has also become prevalent in the software development industry with lots of use cases. While developers are leveraging AIs to expedite and automate many development processes, software with AI-driven techs is also increasing. 

There are lots of frameworks and platforms that developers use in software development with artificial intelligence. This blog shed light on some of the most popular AI tools to develop artificial intelligence software. 

The Role of AI in Developing Software for Businesses

Artificial Intelligence is one of the most innovative technologies today that is being used in many areas. Software development is not an exception to this transition and the role of AI in this field is increasing at a rapid pace. 

Artificial Intelligence and Machine Learning help businesses develop smart software solutions that add tons of advantages to their businesses. One of the most significant benefits of AI is automation. Businesses can utilize AI to automate their processes with AI-driven solutions. The best example of this is chatbots. 

Providing quick and satisfactory customer service is key to winning your customers. Chatbots help businesses offer a convenient method for their customers to address their issues swiftly and provide relevant information. 

Chatbots can interact with customers in a human-friendly way and they can do conversation just like real humans. Similarly, AI is used for data analysis. Analyzing the data to get important insights is crucial for decision-making in a business. AI-driven data analysis provides more accurate information to make predictions. 

Natural Language Processing (NLP) is another advantage of AI to process human languages and output results. There are lots of mobile apps that use NLP such as user assistant which includes Google Assistant, Cortana, and Siri. You can leverage the best mobile app development services to create the next-gen app with NLP. 

There are many trends with artificial intelligence that are setting new levels for businesses. 

Top Artificial Tools for Software Development


1. TensorFlow

One of the most sought-after artificial intelligence software development libraries is TensorFlow. It is an open-source and free library for machine learning and AI projects. TensorFlow is developed by Google and has amazing features to develop AI applications.

As an end-to-end platform, TensorFlow makes building and deploying machine learning models a breeze. It offers plenty of AI tools for numerical computation used to make future predictions accurately. 

Advantages of TensorFlow 

  • It has the complete ecosystem to solve complex real-world problems with ML. 
  • The library offers abstraction to solve a myriad of problems easily. It offers a high-level Keras API to develop and train machine learning models easily.
  • You can get more flexibility with eager execution that offer easy debugging and instant iteration. 
  • With TensorFlow training and deploying machine learning models is easy regardless of the targeted platform and programming language.
  • You can use the TFX pipeline to implement ML models across multiple platforms.
  • TensorFlow Lite is designed to run on mobiles and edge devices.
  • It offers a set of add-on libraries like Tensor2Tensor, Ragged Tansors, BERT, etc. 

Top Companies Using TensorFlow

  • Coca Cola
  • Google
  • DeepMind
  • Intel
  • Twitter
  • Airbnb

2. Scikit Learn

The next prominent artificial intelligence software development tool is Scikit-Learn. It started as a Google Summer of Code project and later became available to the developer community. This is quite a useful project for creating solid software to generate predictive models and provide crucial insights based on deep analysis. 

It supports several supervised learning calculations including K-means, decision trees, bunching, direct and calculated relapses, etc. Scikit Learn is created upon Python libraries like SciPy and NumPy and matplotlib. It’s open source with a BSD license. 

Advantages of Scikit Learn

  • Scikit-Learn is more than sufficient for beginners in machine learning. This is because when they need extra support in creating more complex algorithms.
  • Many calculations are available out-of-the-box with Scikit-Learn like relapse, order, bunching, etc. They are enough for basic AI and data mining projects. 
  • It is accessible to every type of developer and can be used in different contexts. 

Top Companies Using Scitkit-Learn

  • Spotify
  • J.P.Morgan
  • Inria
  • Evernote
  • Change.org

3. BigML

BigML is another great machine-learning platform to develop smart software and applications. This artificial intelligence tool makes building machine-learning models simple and quick. It provides lots of algorithms to solve problems. 

With BigML, you can solve many problems for your company with a single and standardized framework. This platform helps you avoid maintenance costs, complexity, and technical debt as there is no dependency on various libraries. 

Advantages of BigML

  • BigML is suitable for creating predictive analysis applications for various industries like energy, automotive, transportation, pharmaceuticals, IoT, healthcare, and more. 
  • It supports supervised and unsupervised learning algorithms like topic modeling, linear regressions, deep nets, cluster analysis, Principal Component Analysis, and more. 
  • BigML provides instant access to machine learning for on-premises systems or in the cloud. They can be accessed via REST API and web interface. 
  • The platform makes the interpretation of predictive models easy by providing data in a visual format. 
  • It allows the export of models in JSON PML format. 
  • It can be used with various programming languages. 
  • This platform is useful to make a fusion of artificial intelligence and mobile applications
  • Effective automation tools and deplorable on multiple platforms.

Top Companies Using BigML

  • Pfizer
  • Avast
  • Faraday
  • Clairo
  • Mazda

4. PyTorch

It is one of the greatest machine learning frameworks to build AI software for your business. PyTorch is based on the Python programming language and is widely used to create predictive machine learning models and other types of solutions for making critical decisions. 

PyTorch offers flexible and quick experimentation and quick production with an extensive ecosystem of tools and libraries. Besides this, it offers distributed training and an intuitive front end. Installing is very easy with a pip command or installer. You can hire an artificial intelligence software developer to leverage this framework for creating robust AI solutions for your business. 

Advantages of using PyTorch

  • Two execution modes are supported with PyTorch: Graph mode and Eager mode. 
  • It provides more flexibility in eager mode with TorchScript.
  • It easily transitions to graphs in C++ runtime environment providing enhanced speed and optimization. 
  • With the TorchServe tool, PyTorch becomes more scalable. The tool can work in any environment or the cloud and offers features like metrics, multi-model serving, creation of RESTful endpoints, and more. 
  • It also offers APIs for the integration of machine learning into mobile applications. 

Top Companies Using PyTorch

  • Amazon Advertising
  • Salesforce
  • Stanford University

5. H2O.ai

This is an open-source machine learning platform specifically designed to meet the requirements of enterprises. H2O supports popular machine learning and statistical algorithms such as deep learning, gradient-boosted machines, and generalized linear models. 

H2O can be set up with existing big data infrastructure. Alternatively, you can use it on Kubernetes Clusters, Yarn, Spark, and Hadoop for data mining. This platform is capable of fetching data directly from Azure Data Lake, Spark, HDFS, S3, and other sources of data. 

This is one of the best and most comprehensive platforms that you can utilize for artificial intelligence software development. 

Advantages of using H2O

  • H2O has created machine learning algorithms to work with distributed computing. These algorithms like Random Forest, XGBoost, Word2Vec, GBM, etc, are also provided for supervised and unsupervised learning methods.
  • You can create ML models in graphical or coding methods. It allows you to build models using any programming language including R and Python. Its interactive graphical interface lets you build models without coding.  
  • AutoML automates ML workflows including training and tuning of models. 
  • It encompasses distributed in-memory for storing and processing large amounts of data. 
  • Models are easy to deploy with POJO and MOJO models. 

Top companies using H2O.ai

  • AT&T
  • IFFCO Tokio
  • AES
  • USCF Health
  • Commonwealth Bank

6. Keras

Keras boasts to be a human-friendly machine-learning framework that follows a minimalistic approach to development. It reduces the burden on the developers by following the best practices that reduce cognitive load. Hence, it offers a simple and consistent API. 

It provides error messages that are clear and actionable along with eliminating unnecessary user actions in common use cases. With great documentation and a guide, understanding Keras becomes easy and convenient. 

Advantages of using Keras

  • Keras offers an unparalleled benefit to developers in artificial intelligence software development. 
  • It focuses on the speed of debugging code, maintainability, deployment, and conciseness of code. 
  • The codebase is lightweight, easy to iterate, and readable with Keras. 
  • Autograph optimization and XLA compilation make your models run at a faster speed.
  • Models can be easily deployed on a mobile, server, web, or any other platform.
  • It is built on TensorFlow and is compatible with various TPUs and CPUs. 
  • With the mobile app development service, you can deploy Keras on Android and iOS devices. 
  • As Keras is associated with the TensorFlow ecosystem, it works with every phase of the machine-learning workflow whether data management, deployment, or anything else. 

Top companies using Keras

  • NASA
  • CERN
  • NIH

7. Microsoft Azure AI Platform

One of the top tech giants Microsoft offers a myriad of AI services that developers can use to create robust artificial intelligence software. With Microsoft Azure AI, you can create innovative AI solutions for your business with its flexibility and responsible Artificial Intelligence practices. This platform offers various AI models related to language, vision, decision-making, and speech via API calls. 

Developers can create AI applications using Jupyter Notebook and Visual Studio Code. You can use this platform with other frameworks like PyTorch and TensorFlow to build AI-driven applications.

Advantages of using Azure AI

  • It allows developers to build custom artificial intelligence models. 
  • Azure AI can be integrated with tools like GitHub and Visual Studio.
  • It is a scalable platform to develop and deploy AI solutions.
  • There are tools for cognitive service, deep learning, and ML. 

Top companies using 

  • Gartner
  • IDC

To Summarize

Businesses need efficient tools and platforms to build AI applications. Artificial Intelligence is taking its grip on every sphere of human life. Therefore, investments in AI software development are rising. We have discussed the top tools to develop AI software in this blog that you can use in your project. 

If you are planning to develop an AI-based mobile application or software, MobileCoderz is a reliable partner. We are a leading artificial intelligence software development company to help you build secure, scalable, and cutting-edge solutions. We have a team of experienced and professional AI engineers.

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