How to Create an App Using AI/ML for Your Business?

How to Create an App Using AIML for Your Business
Artificial Intelligence has taken center stage in advanced technologies and trends, basically, everywhere. Tech giants such as Amazon, Microsoft, Google, and Apple have integrated AI into their tech stack. In fact, they are providing tools for businesses to incorporate AI algorithms into their software. Enterprises across different business verticals can now deploy AI for social media engagement, customer relationship management, mobile applications, and more. Hiring expert AI and Machine Learning services to help you get familiar with AI for your business or mobile applications is the first step toward the AI space.
It’s not that AI and ML are new and have never been implemented before. It is present on our mobile applications. Some typical examples are-
  • Detecting faces in photos and videos
  • Speech to text conversion
  • Chatbots and virtual assistants
  • Captcha breaking
  • Product recommendations system
  • Object or face detection while taking a photo
  • Classifying images for parental advisory
  • Programming platforms to build AI-based mobile apps
  • Spam filtering in emails
  • Stock price movement prediction and so on.
Once you have an idea about AI and its benefits, you’ll know the point at which you can apply it to your mobile app and if it will help you in your business growth. Let’s get into how to create an app using AI/ML for your business.

How to create a mobile app using AI/ML for your business?

To create a mobile app using AI/ML, you need a well-thought process so as to optimize time, cost, effort, and resources. Since it is an AI-based app, the costs and the time required for app completion definitely go up. But proper planning at each stage will ensure app completion within your budget and time. Let’s see the basic process pipeline to ensure the best results.

1. Plan your requirements

Just because the trend is AI/ML, you cannot be blind and incorporate advanced features in your app. First, ask if AI/ML is essential? How will it improve user experiences? Is it going to solve a challenge? Is the investment worth it? If including AI/Deep Learning in your mobile app makes your app stand out from the competition, and if it offers value to the customers, it is worth considering. Identify the problem and how AI will help it.

2. Contact reliable resources for the job

Once done with the planning, contact reliable mobile app development services that are experts in AI/ML. Tell them your requirements. They’ll come up with the best solutions. Create a list of product requirements and document them. It’ll help them determine the purpose of AI in the app and the technologies needed for it.
One thing to be taken care of is that the mobile app company should be well-versed with AI/ML technologies. Before selecting one, ensure that they check the right boxes.
  • Identify their areas of expertise
  • Analyze their customer service
  • Study their portfolio
  • Get in touch with their representative and test their promptness
  • See how efficiently they resolve your queries.
  • Talk to them about the time required for project completion, the expertise of the resources available, and the costs.

Make decisions based on the above factors. Houston IT Developers provides AI/ML-ETL development services through an expert team that has worked on projects involving advanced deep learning technologies. You can hire us if you plan to build an AI-based mobile app.

3. Mobile app designing

Once you’re settled with the AI and Machine Learning services, it’s time to get into the most crucial task, app designing. Your vendor will decide the required tech stack based on your app’s needs. Make sure you convey your requirements clearly and well in advance for them to pick the correct framework that supports your app needs. Let’s discuss some popular AI/ML/Deep Learning software tools needed to develop a mobile application. The choice of AI technology depends completely on the company’s business requirements.

AI/ML tools, libraries, APIs, and platforms to create AI-based mobile apps

An artificial intelligence-based mobile application is hard to build and requires proficient AI/ML-ETL development services. Typically, Python, Java, and C++ are used as programming languages for AI-based applications. But now, third-party AIaaS (AI as a Service) products are available that make designing AI-based mobile apps easy and affordable. The most popular products are-

Microsoft Cognitive Toolkit (CNTK)

The Microsoft Cognitive Toolkit (CNTK) is a deep learning open-source library for machine learning and deep learning. Created as a training algorithm for machines to learn like humans, it can be used to create various ML models. It makes it easy for neural networks to process large amounts of unstructured data. Developers can select the metrics, networks, and algorithms and customize them as per the app requirements.

Amazon ML in AWS (Amazon Web Services)

Amazon has the AWS Deep Learning Containers (DL Containers) that support ML frameworks and make it easy to deploy and optimize the ML environments. The DL Containers have pre-packaged Docker images to deploy MI frameworks such as TensorFlow, PyTorch, and Apache MXNext in minutes. The developers can add their own libraries and tools on top of these images for a higher degree of data processing, compliance, and monitoring.

TensorFlow Mobile

TensorFlow is an open-source platform (library) consisting of an ecosystem of tools, libraries, and community resources that helps developers build and deploy MI-powered applications. Keras, an open-source library written in Python has been integrated with TensorFlow. It is a product of Google developed for deep learning applications. This library provides a high-level API and has integration with Java and R. It supports GPUs (Graphical Processing Units) and CPUs (Central Processing Units). It offers faster compilation than other deep learning libraries.


PyTorch is an optimized library effective in creating Deep Learning applications. It is based on Python and Torch and is preferred over TensorFlow since it uses dynamic computational graphs and completely uses Python language. It uses tensor computation to make operations faster. A tensor is a container that can hold data in multiple dimensions. PyTorch also has the Automatic Differentiation feature for creating and training deep neural networks.

Apache MXNext

The Apache MXNext is another popular open-source Deep Learning framework used to train and deploy neural networks on a wide array of devices from cloud infrastructure to mobile devices. It has toolkits and libraries for computer vision, natural language processing, time series, and more. Its supported languages include Python, C++, R, Matlab, and JavaScript.

Other popular AI/ML frameworks are H2O, Petuum, Polyaxon, DataRobot, NeuralDesigner, Apple Core ML, Caffe2, and PredictionIO. To start building your AI-based apps, you need powerful SDKs and APIs. Third-party tools like Microsoft Face API, Google Vision API, and Apple’s SiriKit are some examples. The right AI platform for your app depends on the capabilities you want to incorporate into your app. Hire reliable AI and Machine Learning services and talk to their experts regarding your requirements. They will decide the most appropriate software needed to build an AI/ML mobile app.

A special word on data for AI-based mobile apps. Typically, data is the epicenter of AI/ML applications. It needs a large amount of relevant data. Ensure you have a good data mining and modeling technique in place. The better quality data you provide, the better outcome you can expect from the AI algorithms.

4. App testing and launch

If you want to go for an MVP (Minimum Viable Product) or a full-scale app is your call. As per our suggestion, go for an MVP first. It saves you time and money. Test the app and look for errors and bugs before you go for the soft launch. Now, ask for feedback from the audience. Don’t rush to make a full launch. Sometimes, it takes 4-6 months for the app to be completely ready after the soft launch. A fully-functional app is always better than a bug-loaded app because if the user is not satisfied, it is difficult to bring them back.
Once you have a full launch, invest in updates and improvements. And ensure you provide good customer service.

Do you need to create an app using AI/ML for your business?

We are sure the above points will guide you to get it started. You can always depend on Houston IT Developers for mobile app development services involving AL/ML-ETL technology.
If you have any queries regarding AI for your app, you can contact us, and our experts are always ready to guide you.