The Top 5 AI Tools for Software Developers

Marketing ScreamingBox, Thursday, August 22, 2022

In the past, Artificial Intelligence was considered a tool that only industries could leverage for better productivity and reduced costs. But businesses are now opening their eyes to what employing artificial intelligence could mean for them when it comes to ROI, customer experience, productivity, reduced risk and problem-solving. 

In fact, roughly 47% of digitally mature companies were reported to have a specified artificial intelligence strategy. Also, about 54% of CEOs believe that artificial intelligence technologies adopted in their organizational processes have already boosted their performance.

Why software developers need AI

Software applications make a large contribution to the everyday activities of enterprises. As a result, the employment of software has grown, from browsing for a product on the internet inventory management to emailing clients and co-workers. 

But, as much as the technology is a powerful and revolutionary invention, developing it is a tricky task that necessitates concept generation, product definition, strategic design, coding, quality assurance, and coding. If anything were to go wrong, you might have to start from afresh to remedy the error.

For this reason, several firms are incorporating artificial intelligence for quality results to combat this and the obstacles that come with the conventional software development process.

Types of AI for software developers

You can categorize AI into two forms: Weak AI and strong AI. 

● Weak AI– The application of sophisticated algorithms to specific problem-solving activities that do not need the complete range of human cognitive capabilities. Siri and Alexa, for instance, are instances of voice-based personal assistants.

● Strong AI– This is a system with human-like cognitive functions. It can finish tasks, seek and create solutions without human interference. For example, a self-driving vehicle employs a combination of computer vision, image recognition, and deep learning to steer the car in a particular route while avoiding unforeseen scenarios such as pedestrians.

As you can see, AI is a handy tool for any business or software developer. Now, let us look at the top five AI tools that a software developer would enjoy.

AI tools for software developers

1. Google ML Kit

The Google ML Kit is by far the most widely used AI-enabled software development tool in the tech world. It is designed to empower app developers to build unique and advanced features for iOS and Android mobile phones. 

Also, it allows mobile app developers to combine machine learning algorithms with a plethora of APIs based on mobile applications running on the device or in the cloud.


       Face and text recognition

       Barcode scanning

       Image tagging

       Offline functionality

2. IBM Watson

This is one of the finest AI-driven software development tools for developers looking for faster and more efficient solutions. Watson is pre-integrated and pre-trained on a versatile database schema that has been tailored to quicken AI creation and adoption. 

It offers developer tools that streamline integrating chat, language and search into your apps. Watson provides the client with precise developer resources for, among other things, speedier reporting, increased R & D, enhanced interactions, anticipating market trends, and mitigating risks.


       It aids businesses in: 

       Making more accurate forecasts

       Automating operations

       Interacting with users and consumers

       Augmenting knowledge

3. Tensorflow

It is an end-to-end open-source machine learning framework. It features a rich, adaptable ecosystem of tools, libraries, and community resources that enables software developers to design and launch ML-powered apps seamlessly. 

Organizations can effectively train and deploy models in the cloud, on-premise, the browser, or on-device using Tensorflow. It constructs and trains machine learning models with the help of highly accessible high-level APIs.

Tensorflow is designed to power machine learning applications with agility, speed and precision while preventing high overhead costs.


       Leverages several linear algebra routines for indexing, type-casting, cloning, slicing, sharing storage

       N-dimensional arrays

       Functional GPU support

       Numeric augmentation routines

       It is embeddable, with ports for Android and iOS backends

       Excellent interface to C (via LuaJIT)

4. H20.AI

H20.AI is an open-source distributed in-memory machine learning solution powered with linear scalability. It is a business-focused AI software that facilitates data-based decision-making and the generation of actionable insights. 

There are two versions of H20.AI: regular H20.AI and the premium version known as Sparkling Water.

H20.AI supports the most used statistical and machine learning algorithms, such as gradient boosted machines, generalized linear models, and deep learning. Also, it can automatically import data into its in-memory distributed key-value store from HDFS, Spark, S3, Azure Data Lake, or other data sources.


       It supports programming languages such as Java, R, and Python

      It runs on existing big data architecture, including bare metal and Hadoop, Spark, and Kubernetes clusters

       Seamless deployment


      Data analysis

       Customer intelligence

       Risk analysis

       Fraud detection

       In-depth analytics

       Digital healthcare

5. Infosys NIA

Infosys is a cutting-edge Artificial Intelligence Platform designed by combining Infosys Mana’s AI platform and AssistEdge’s Robotic Process Automation (RPA) solution. First, it accumulates organizational data on legacy systems, people, and processes. Then, it populates it in a self-learning knowledge pool that a team of software developers and data analysts can use to build highly efficient and scalable ML models.

Users do not need data science skills to use this software, thanks to the platform’s user-friendly ML workbench.


       Organizational knowledge dissemination

       In-depth analytics

       Service automation

       Automated incidence analysis


       Projecting revenues

       Anticipating future product trends

       Identifying and predicting customer behavior

       A thorough analysis of the fine-print of contracts and legal documents

       Recognizing compliance and fraud

These are some of the ideal AI software development tools that have garnered a strong foothold and are poised to revolutionize business operations and digital product innovation. Without a doubt, AI is the future of business. 

If you want to achieve originality, profitability, and top performance, your first step should be integrating AI-based solutions. Understanding and using these tools will make you a top pick for clients as a software developer. 
Are you looking to transform your business by integrating cutting-edge technology in your business operations? Then, check out ScreamingBox – We provide digital development work for all businesses, including Startups, R&D Labs, SMBs, and enterprise companies.

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