Today many people across the world are increasingly moving to smartphones. While doing so, they are also embracing a new concept: intelligent mobile apps. People are using these apps for quick task execution with little touch and also to have information for making key decisions.

What are these intelligent mobile apps anyway?

Intelligent apps get real time and historical data from customer interactions to give suggestions and make predictions. These apps have machine learning and data analytics as the core features. The predictive analysis capabilities of these apps make it possible for them to get user’s needs and provide suggestions accordingly.

Features

These apps have a wide variety of features that make them useful in both B2C and B2B situations.

• Ability to work on vast amount of data and work on a lot of human interactions.
• Combination of process and sensory inputs using IoT to provide crucial insights.
• Adaptability to many situations by learning.
• Ability to do the job by reading gestures, motions and speech of users.

Examples of top intelligent mobile apps

A number of companies are coming up with intelligent mobile apps today. Some of these apps are:

1. Cortana: Developed by Microsoft, this app is a personal assistant offering a variety of features like setting reminders, weather forecast etc.
2. Alexa: Amazon came up with this virtual assistant app that can do a variety of tasks like setting alarms, playing audiobooks, providing news updates etc.
3. Socratic: This Google app helps students learn by enabling them to ask questions which it answers by providing suitable blog links, YouTube videos etc.

Industry use cases

Here are just some of the examples of intelligent mobile apps being used in different industries.

1. Healthcare: Apps help patients find the nearest doctor, book appointments, remind about medications etc. They help doctors with status of consultations, equipment availability etc.
2. Fintech: In fintech industry, intelligent mobile apps are used by companies to attract millennial customers. The aps analyse the spending patterns of users and suggest budget management tips. They can also check the history of company stocks and advise whether to invest in a stock or not.
3. Education: Apps are helping students make notes in various forms like speech, text and images.

Requirements for creating intelligent mobile apps

There are certain technology requirements that need to be kept in mind while creating intelligent mobile apps. They are:

• Data lake that can support real time data gathering, safe data management and flexible data delivery options.
• Data-as-a-service capability allowing user self service, simple data discovery and integrated data alignment.
• Analytics capabilities and real-time maintenance of data records for decision making.
• Agile development with devops and PaaS techniques.

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