7 Best AI Software Development Tools: A Comprehensive Guide for Success

Developing software involves a multitude of intricate processes such as ideation, product definition, coding, strategic designing, quality assessment, and more. To improve outcomes and tackle these challenges, many leading organizations are turning to artificial intelligence (AI) and machine learning (ML) tools.

AI Software Development Tools

Here are some of the best AI software development tools available for developers:

1. Google Cloud AI Platform

This platform offers a comprehensive toolchain to expedite the development and deployment of machine learning projects. It enables you to build portable ML pipelines with Kubeflow and offers various options to store data. It provides pre-configured Virtual Machines (VMs) for developing deep learning applications and includes natural language processing (NLP) capabilities.

2. Microsoft Azure AI Platform

A robust cloud platform, Microsoft Azure AI has many advanced capabilities such as object recognition, unsupervised machine learning, speech recognition, and more. It offers domain-specific pre-trained AI models and provides various machine learning services like Azure ML, Azure Databricks, and ONNX.

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3. IBM Watson

Equipped with advanced AI capabilities, IBM Watson is popular for its mobile app APIs, conversation interfaces, and NLP services. It offers AI development services that help developers build apps with pre-trained AI capabilities and provides integrated tools such as Watson Assistant and Watson Natural Language Understanding (NLU).

4. H20

An open-source, machine learning platform, H20 offers smart machine learning algorithms, statistical and generalized linear models, and deep learning models. It supports big data, Hadoop, and Spark/Kubernetes clusters and allows the use of programming languages like R and Python for model building.

5. TensorFlow

An open-source, machine learning library, TensorFlow provides comprehensive tools and libraries to accelerate AI development. Businesses can use it to train and develop smart ML and AI-powered applications for various complex operations.

6. MxNet

A deep learning framework, MxNet helps enhance AI development with advanced NLP capabilities. It offers distributed training models to scale AI applications and is often used in Multi-GPU and multi-machine training.

7. Infosys Nia

With Infosys Nia, you can build powerful AI-powered apps using its wide range of machine learning algorithms. It enables you to create chatbots, automate actions with a conversational interface, and even integrate robust analytics solutions.

By utilizing these AI development tools, you can effectively improve the quality, speed, and scalability of your software development projects.

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