AI tools are changing the way we work every day. Here, we bring you the top AI tools for mobile app development.
Top AI tools for web app development
AI tools are revolutionizing web app development.
Using AI tools will increase your productivity at every stage of the development process.
They’ll also help you create innovative features that’ll help you set yourself apart from your competition.
If you’re a software engineer looking for ways to improve your productivity and create better web apps, the AI tools we’ll discuss here will help you do that.
Table of Contents
Amazon CodeGuru is an AI-powered static application security testing (SAST) tool that uses machine learning and automated reasoning to identify vulnerabilities in your code.
It also provides recommendations on how to fix those vulnerabilities and tracks them until they’re resolved.
It has two modes – Reviewer and Profiler.
CodeGuru Reviewer detects potential vulnerabilities and defects that are hard to find with only human review.
CodeGuru Profiler gives you interactive visualizations and recommendations to fine-tune your web app’s performance.
It can also troubleshoot operational issues using your app’s runtime data.
CodeGuru works with these repositories:
- AWS CodeCommit
It’s also easy to use.
All you need to do is open the CodeGuru console, associate it with your repository and you’re ready to go.
You can use CodeGuru for free for 90 days, after which you’ll have to pay.
What you pay after that depends on the size of your repository and your specific needs.
Azure Machine Learning
Azure Machine Learning is a cloud service for training, deploying, and managing machine learning models.
As the name suggests, it’s a part of Azure, Microsoft’s cloud computing platform.
Azure ML is an end-to-end platform for machine learning operations (MLOps).
So, you can create and train your own machine learning models with Azure ML before deploying them.
source: Towards Data Science
Then, you can use it to manage your models throughout your web app’s lifecycle.
You can also use models from open-source libraries like PyTorch or TensorFlow.
Azure ML allows you to quickly deploy models with their automated machine learning model builder.
Azure ML offers a pay as you go model as well as custom pricing models based on your organization’s specific needs.
We’re all familiar with ChatGPT at this point.
When used right, it’s a powerful tool that can help you speed up your web app development.
As it’s a large-language model (LLM) chatbot, it can’t build your app for you – yet.
So, how can you use ChatGPT to help you build a web app?
One way you can use it is to generate boilerplate code and short code snippets to speed up your workflow.
You can also use it to debug your code and identify any mistakes you’ve made when writing the code.
source: Built In
A great way to use it is getting feature ideas for your app.
Let’s say you’re building a health-tracking web app.
You can ask ChatGPT: “You’re building a health-tracking app. Which features would you add?”
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It’ll then list out the features it thinks you should include in your app.
From there, you can move on to feature prioritization and decide which features you’ll include in your minimum viable product (MVP).
And it can do all this in just a few seconds, just from natural language prompts.
ChatGPT operates on a freemium model – GPT-3.5 is free to use, but if you want to use the more capable GPT-4 model you’ll have to upgrade to ChatGPT Plus for $20/month.
Github Copilot is a coding assistant that turns natural language prompts into coding suggestions.
It works with most popular programming languages, such as:
It also easily integrates into the most common integrated development environments (IDEs) for web development, like Webstorm.
Github Copilot offers AI-based suggestions based on your code’s context and style conventions.
source: Venture Beat
Github Copilot’s main strength is that it automates the writing of boilerplate code.
This’ll let you focus on more important and complex tasks.
Engineers who use Copilot agree with that, too.
Github researched how Copilot impacts their users’ productivity and found that:
- 74% say they can focus on more productive work
- 88% feel more productive
- 96% are faster with repetitive tasks
One drawback is that it can’t test the generated code to see if it works.
You’ll have to make sure it works before using it.
Github Copilot offers several billing plans, with Copilot for individuals priced at $10/month or $100/year while Copilot for business is $19 per user per month.
Otter.ai is an AI-powered tool that records and transcribes conversations in real-time.
It’s impossible to remember everything that happens in a meeting and transcription can take up valuable time.
That’s where Otter.ai comes in.
Otter.ai can automatically join your meeting on Teams, Google Meet or Zoom and start transcribing.
Let’s say you’re writing a requirements document for your web app and you want to double-check something that was discussed during a previous meeting.
And you’ve only recorded the meeting and haven’t transcribed it yet.
Normally, this would mean you’d have to transcribe the meeting or find the exact timestamp in the recording when the discussion happened.
If you use Otter.ai, you’ll have the transcription ready in real-time and finding that information would be a breeze.
And that’s just one scenario in which Otter.ai saves you time and increases your productivity.
Otter.ai operates on a freemium model, offering a free Basic tier as well as several paid plans.
Otter.ai Pro, for individuals and small teams, is $16.99/month per user ($8.33/month if billed annually) while Otter.ai Business is $30/month per user ($20/month if billed annually).
They also offer custom enterprise solutions to suit your organization’s specific needs.
Snyk is an AI-powered SAST tool, similar in function to Amazon CodeGuru.
It can scan your code, identify vulnerabilities and suggest fixes that won’t introduce new issues.
A good way to think about it is that it’s like Hemingway or Grammarly for code.
Snyk doesn’t just scan your code.
It can also scan:
- Docker containers
- Infrastructure as code (IaC)
A major advantage of Snyk is that you can easily integrate it into your workflow.
source: Snyk User Docs
It can work with most major IDEs and repositories.
Also, it can analyze code written in most of the common programming languages.
Snyk operates on a freemium model, with a free plan that limits the number of tests you can run each month.
The Team plan starts at $87/month per developer, $79/month per developer if billed annually.
Also, they offer custom enterprise plans tailored to your needs.
Tabnine is an AI-powered code completion assistant, similar to Github Copilot.
It’s powered by proprietary machine learning models trained on open-source code with permissive licenses.
One major advantage of Tabnine is that you can train it on your own codebase.
And it does it while ensuring the privacy of your code, as it can run in a fully isolated mode.
With Tabnine, you can write whole lines of code with just one keystroke and generate an entire function without ever having to exit the editor.
Also, Tabnine can turn natural language prompts into code suggestions.
All you have to do is describe what you’re looking for and it’ll suggest the right code to use.
Tabnine supports dozens of IDEs and programming languages, making it a very useful tool for almost every engineer.
Tabnine offers a free Starter plan with only short code completions and limited functionality.
They also offer a Pro plan at $12/month per user, that can support up to 100 users, as well as a custom enterprise solution.
TensorFlow is an open-source library for building and deploying machine learning models.
It specializes in the training and deployment of deep learning models.
You can use one of their pre-trained models or create a custom model for your web app.
TensorFlow.js is specifically designed for web development.
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TensorFlow.js can create and train models that’ll power features like:
- Personalized recommendations
- Image processing
- Text recognition
For example, Twitter used TensorFlow to develop a model for its ranked timeline feature.
Swisscom also used TensorFlow models to optimize their customer support operations by determining the intent of their users’ inquiries.
As TensorFlow is open-source, it’s free to use for research and commercial purposes.
Uizard is an AI-powered UI design tool you can use to create a rapid prototype in seconds.
With Uizard, you can make:
You can choose one of their UI templates and refine them to suit your needs.
Also, you can create a new design from scratch using Uizard’s pre-made design elements.
You can even create designs from natural language prompts.
Uizard also supports real-time collaboration.
So, your whole team can work together and share feedback as you’re creating the design.
You can also turn the wireframes you’ve collectively designed into high-fidelity mockups in seconds.
Uizard can also turn your hand-drawn wireframes into customizable UI designs.
It has several pricing options, including a free version for students and hobbyists.
Uizard Pro is $19/month, $12/month if billed annually, and Uizard Business is $39/month.
They can also provide custom enterprise solutions, based on your specific needs.
Zecoda is an AI tool that turns design files into working code.
All you need to do is upload a Sketch or Figma file and Zecoda will turn it into front-end code for your web app.
This makes the job of turning your designs into a fully functional web app a breeze.
What’s unique about Zecoda is that it’s an AI tool with a human touch.
All outputs are checked by one of Zecoda’s engineers.
Still, this process is much faster than if you did it yourself.
Zecoda is currently in closed beta testing which you can sign up for on their website.
If you don’t want to be left in the dust, adopting AI tools is the way to go.
The AI tools we’ve covered here are just a small sample of the tools you can use to increase your productivity and improve your web app in the process.
To recap, some top AI tools for web app development are:
- Amazon CodeGuru
- Azure Machine Learning
- Github Copilot