In this fast-changing technology environment, technologies which are shaping the world are itself changing rapidly and getting replaced by new technologies.
In such a rapidly changing environment, you are concerned about the right selection of technology for your startup.
Aren’t you?
Yes, you should be. Because, right technology which suits your requirements can save you time, energy and money.
Through this article we would compare two technologies ‘React’ and ‘Angular’ and will try to find out which one is better for your application.
‘React’ and ‘Angular’ are two of the most popular web technologies in 2019, as per Google Trends.
Angular is a JavaScript framework, developed and maintained by Google. On the Other hand, React is a JavaScript library, developed and maintained by Facebook.
Both of these technologies are growing and their future looks bright. That means you won’t regret using any of these.
But, which one is better?
Or
Are they equally good?
Let’s find out.

Framework Vs. Library

Angular is a full-fledged framework that offers strong opinions on how to structure your application. Which means you have less flexibility and you need to use what Angular provides.
React on the other hand gives you much more freedom, you can choose any of your own libraries which also means that you will have to take care of respective updates and migrations by yourself.
So, Angular is Opinion based, it’s why less flexible but in React, you will have to find the best third party code for many basic things like routing.

Features

Angular provides the following standard features:
  • Dependency injection
  • Routing, provided by @ angular / router
  • Templates, based on an extended version or HTML
  • @ angular / forms for building forms
  • Ajax requests using @ angular / common / http
  • Component CSS encapsulation
  • Utilities for unit testing components
  • XSS protection
React provides the following features:
  • No dependency injection
  • Instead of classic templates, it has JSX
  • State management using setState and the Context API
  • Utilities for unit testing components
  • XSS protection.
Both are rich in Open Source Resources.

Templates – HTML or JSX

Angular uses templates which are based on HTML with Angular directives. React combined UI templates and JavaScript logic, which is termed as JSX. It’s an XML-like language.
For working on React, you just require knowledge of JavaScript, but for Angular, you will have to learn its specific syntax.

Components

The web is gradually becoming component based. A Component receives an input and after processing some internal logic returns a rendered UI template.
Easy to use components can be used within other components or even in other projects which make the development of web applications faster.
Both Angular and React are component based.

Learning Curve

Learning Curve for Angular is slightly higher than that of React.

For learning Angular, you will have to get comfortable with the TypeScript. For developers who have experience with statically typed languages ​​such as Java or .NET, this would be easier to understand compared to JavaScript.
Angular framework is very rich in options to learn from; like Modules, Dependency Injection, Decorators, Components, Pipes, Services, Templates and Directives. In Addition to these, there are more advanced topics such as Change Detection, Zones, AOT Compilation and
Rx.js.

For Learning React, the first thing you would encounter is JSX. These are expressions which are actually JavaScript and some special HTML like syntax. You will have to learn components, use props for configuration and manage internal state.

Although, you are not required to learn any new logical structures or loops since they are based on JavaScript.
Entry barrier for Angular is higher than for React.

Mobile Solutions or Angular Vs. React

Both of them provide solutions for creating Mobile Apps.

Through Ionic Framework, you can create hybrid mobile applications. It uses a Cordova container which is incorporated with Angular.
Facebook developed React Native platform which can be used for creating truly native Mobile Apps.

Ionic based Mobile Apps are simply a Web Application inside or a native Web view container, on the other hand, React Native can be used for producing a truly Native UI.

I think I helped you understand React and Angular better.

Both are good for Medium to Large size applications. Selection of any of these will depend on your specific requirements.

You can take your decision based on the following factors:

Choose a framework on which you have experience

Experience in technology will really save you time, energy and money. If you or your teammates have more experience with Angular choose it about React and vice versa.
If you or your teammates are a learner, you may put some time daily into learning new technology, putting the latest technology into production in a short time without any prior experience or support can be a nightmare.

If you want expert advice in this regard, you can reach us (Link to Contact Form).

Check your Market Requirements

If you are serving B2C market, with millions of potential customers, it’s good to optimize your application as low as possible, reducing your network calls, PWA, caching etc.
For B2C, React can be a good choice.
If you are building a B2B application or a console application, it’s tricky to go ahead with because you will have customers who would pay up-front and demand best of services.
In this case, a rapid application development framework like Angular, which provides good productivity and ensures a modern web experience, can be a good choice.

Choose a framework with low cost

If money is not an issue for you, you can hire the best of developers to work on any technology.
But, if cost-cutting is your priority, you can start with the technology which suits to your starting team or friends who are helping you in building the application.

You can also outsource your web development work to a good technology partner, it is highly possible that they have already built a similar application, and the cost of your application might come down drastically.

Was this article helpful in finding the right technology for your startup?

If you have any queries on this topic, reach out to us , we would be happy to help you out.

Some of the most successful online businesses started today with perfect MVPs: Dropbox, Facebook, Groupon, AirBnb, and even Amazon.
Dropbox did not even build a product to test their idea. Instead, they created a demo video to check if “file syncing” was interesting to people. They avoided the whole infrastructure and app development as a risk they didn’t want to take. The video was so successful, that in one day, 70000 people wanted to try their idea!
Amazon started out by selling books on a simple website and went on to become the online selling giant it is today. AirBNB started small, with the need to temporarily rent out the founder’s loft: just a few pictures of the founders’ loft for a simple web page got them 3 guests at first.
They all took the MVP approach and later found explosive growth. How do you build a successful product with this approach?

Don’t Rush In
Your team has come up with a product idea that is going to change the industry. Now, all you need is to build a Minimum Viable Product (MVP) to prove the idea, and later, you will build a full, mature, market winning product.
Do you know that an MVP works rarely and that 50% of people taking this approach fail? So how can you be more successful?

Create the Mindset
All creative endeavors involve trial and error and iterations. Whether it is writing a book, creating a painting, or creating a digital product. Designing and writing code can be much more expensive and there is no way to predict if the end product will succeed. So you need to prepare your ground well before you invest time and money.
Think of the MVP more as a process or learning than just a product. The MVP process makes you customer-driven, instead of product-driven, in order to minimize your risk of failure. Use the MVP to learn from your customers to validate your business idea.
The MVP is not just your final product without, say, half or your final list of features. Nor is it a quicker, cheaper way to launch your product. In fact, more than a product, it is an ongoing process or doing things. Learning and implementing is key in this Lean idea. Use it as an experiment in a business process than as a product development process that satisfies a minimum checklist.
In the MVP process, you make some assumptions, and create the smallest possible deliverable to test those assumptions. You use the results of this experiment as feedback to drive the development further. It is a trial and error world, and the earlier you find your errors, the more likely you are to succeed. Go back to your drawing board again and again.

Avoid Incorrect Assumptions
You need to start out with a set of assumptions for an MVP. One of the main assumptions you will make is what users are looking for. You also assume that your design will work for them in the way you think. At the marketing level, you assume a certain strategy. For monetization you assume a certain model. Technically you need to figure out what technology and architecture will work most efficiently and is scalable.
Among all these assumptions, the one most likely to cause failure is: “no market need”. You may spend a lot of budget and manpower in creating something that no one wants.
A way out of this is: as a first step is to go out and talk to customers. This simple act will reveal many facts and you will have tested the most basic assumption with zero investment. If there is interest in the product, then you can learn more about what features to build first, what to build later, and what not to build. Test your MVP with real users as soon as possible. Use the results of this test to iterate your assumptions and design.

What Features to Include
Building an MVP isn’t easy. Some people interpret “minimum viable product” as the smallest imaginable set of features in the product. But minimum cannot be half done or unpolished. In fact, this interpretation might make you miss the opportunity to add a feature that establishes true market differentiation. Or make users easily adopt the product.
In such cases, investing in features makes sense, as they lead to a valuable and differentiating capability that makes you stand out. This is especially true for B2B products and products where there is already competition and you need to outdo them. Your solution must solve the existing problem ten times better.
The MVP must not fall short on providing a good experience and full value.
At the same time, don’t rush to ‘build stuff’. Do your homework. Your spec document or feature list should be based on real interviews with users and potential customers. A poorly thought through prototype is a total waste. Ask questions about user needs, and back all assumptions with user research.

How Minimum?
The MVP is not a beta version or your app or website. Nor is it a few working mockups. You need to make your MVP more like a “Minimum Valuable Product”.
That is, it should address at least one specific audience and one key problem while having a well-designed user experience. A good MVP demonstrates the value proposition, retains the early adopters and provides feedback. As a ballpark, five features is a good number of features to start off with, that focus on solving top user problems at first. Put everything else on the back burner.
In case there are competitors that solve the same problem, find the one feature that will make your MVP stand out.

Iterations
The first version will not lead to much learning. Plan for iterations. In fact, the first few iterations may fail. Incorporate user feedback with the “make – test – learn” approach. Budget for the iteration process. However, as the number of users grows, an hypothesis validated initially with fewer users may also fail.

Technical Excellence
A revolutionary product or solution will often present you with tough technical problems. As a successful example, look at Dropbox’s technical execution. They solved all technical challenges and created a super UX experience. It ‘just worked’ and was so simple, people jumped to use it.
Finding a good execution partner for technical delivery may be a challenge, if you do not have the required skills. Learn how to evaluate your technology partner.
In conclusion, conceptualize and execute your MVP such that it never compromises on value and experience for the end user. Do not just assemble together a list of features, but bring all aspects together holistically to help users achieve their. Iterate often.

Eastern Enterprise: Your Technical Partner
At Eastern Enterprise we are able to help you with the technology skills for building your MVP. We are reliable, innovative and experienced, and specialize in software product development, mobile app development and custom application development in many verticals. With an Agile development process and unique engagement model, we have worked with many clients in Europe, and we can assure you of a successful creation or a cost effective and robust MVP.

Digitization of the world is happening at the exponential rates. As per IDC, a Market Intelligence Company, the world’s data will grow to 175 Zettabytes (1 zettabyte = A trillion Gigabytes) in 2025. We are creating lots of data in each and every field.

But, are we capable of handling and processing this data and draw a meaningful conclusion out of it?

As humans we have limitations of processing the data, that’s where machine learning comes to our rescue.

Machine Learning (ML) is a category of algorithms that allows software applications to become more precise in predicting outcomes without being explicitly programmed.

Its basic premise is to build algorithms which receive input data and use statistical analysis to predict an outcome while updating outputs as new data becomes available. Machine Learning is touching our lives on a day to day basis.

Surge pricing strategy used by Uber uses machine learning to revise the price in real time.

With Machine Learning, systems can now learn from data, identify the patterns and make decisions with minimal human intervention.
Isn’t that great?
Just imagine how far can it take the human race. Artificial Intelligence, the next big revolution, completely depends on how can we make the machines learn certain things. So, Machine Learning is crucial for taking better business decisions through data and live a better quality of life.

How machine learning works

There are two categories of Machine Learning Algorithms, Supervised and Unsupervised.

Supervised

Supervised algorithms need a data analyst or data scientist with machine learning skills to provide both input and desired output. Data scientists determine which all variables or features, the model should analyze and use to develop predictions.

Unsupervised

These algorithms don’t require to be trained with desired outcome data. They use an iterative approach (deep learning) to review data and arrive at conclusions. Unsupervised machine learning algorithms are used for more complex processing tasks than supervised machine learning algorithms.

 

How Machine Learning is helping the ecosystems

 

Product Recommendations

Many E-Commerce companies are using Machine Learning for making product recommendations. ML algorithms use customers’ purchase history and match it against product inventory to identify hidden patterns and group similar products together. Group of products is then suggested to customers which increase the probability of purchase.

Medical Diagnosis

ML helps many healthcare organizations to do almost perfect diagnosis, predict readmissions, recommend medicines and identify high-risk patients. For example, Stanford developed a machine learning algorithm which is capable of diagnosing skin cancer by learning from the data and imaging fed into it.

Financial Analysis

Financial Organizations have large amount of quantitative and historical data. ML is extensively being used for processing this data and do portfolio management, algorithmic trading, fraud detection, and loan underwriting. Future applications of ML in finance include conversational interfaces for security, customers service, and sentiment analysis.

Improving Cyber Security

Machine Learning is allowing providers to build new-generation technologies which efficiently and quickly detect unknown threats.

Predictive Maintenance

Manufacturing firms follow preventive and corrective maintenance practices which are expensive and inefficient. ML helps to identify patterns hidden in the factory data and discover meaningful insights. This predictive maintenance helps in reducing the risks associated with unexpected failures and remove unnecessary expenses.

Customer Lifetime Value Prediction

Companies have a huge amount of customer data which can be used to make better business decisions which ultimately can increase their revenue.
Customer Segmentation and Customer Lifetime Value Prediction are crucial matrices for marketers.
Machine Learning helps businesses predict customer behaviors & purchasing patterns and it also helps in sending the best possible offers to individual customers based on their browsing history and purchasing patterns.

Increasing Customer Satisfaction

Machine Learning can be used for superior customer experience. Client requirement can be correctly assigned to the most suitable customer service executive based on previous call records for analyzing the customer behaviour.
This way, Machine Learning drastically reduces the associated costs and the amount of time invested in managing the customer relationship.

Eastern Enterprise Leveraging Machine Learning

SmartBooqing is the world’s smartest invoice processor. It’s a product developed by Eastern Enterprise leveraging Machine Learning algorithms.
It’s capable of fully automating the accounting systems.
Machine Learning Algorithm developed by SmartBooqing makes it the only invoice processor that can process every invoice, both paper and digital (UBL) at line level.
This way, you can process invoices faster, with high quality and great consistency.

Get back to us if you have any queries regarding Machine Learning or if you want to implement it for your organization.

According to Deloitte Technology Industry Outlook, the General Data Protection Regulation of the European Union (GDPR) requires that technical companies must make architectural and technical changes to comply with the regulations. This is due to the large amount of user data that they contain directly or via their cloud solutions for business customers. However, different industries and companies across Europe are now realizing the technology deficit compared to American and Asian companies and are increasingly focusing on both modernizing and large investments in software development projects. In this article we discuss current trends in the software development industry.

The State of European Tech 2018 recently released their report, which concluded that “while Europe’s general economy and traditional industries are stuck in trouble, fast-growing technology is the best hope for growth.” Some key findings from the report:

$ 23 billion invested only in 2018, against just $ 5 billion in 2013
There were four technical stock market introductions that reached valuations of more than $ 5 billion on the opening day, including Spotify
Europe had three of the top 10 largest technical stock market introductions of 2018 around the world.

Now that we have seen the enormous growth in the software development industry, let’s take a closer look at the rising trends in business models based on Machine Learning from the technology companies and see what impact this has on all industries where they operate, such as healthcare, legally , production, car and agriculture.

Convergence of IoT, AI & Blockchain:
There are a number of expressions currently used to describe artificial intelligence, including machine learning & predictive analysis. Let’s take a look at some of the highlights related to investing in software-based development-based software development projects:
Improves marketing processes and helps with accurate sales forecasts
Accurate medical diagnoses and assistance with treatments
Significant savings in time and personnel costs thanks to a significant reduction in data entry related work / jobs
Real-time customer feedback continuous continuous product updates and augmentation

AI will eventually automate Software Development
Company-wide CRM and ERP systems generate huge data sets for analysis. Software development in Machine Learning / AI aims to synchronize Hardware operating systems, server software and mobile applications to generate insights and patterns to improve product / system performance, profitability and customer satisfaction. When machine learning models are applied to these datasets, IT activity transforms from reactive to predictive to future-proof. When the power of AI / Machine Learning-based software development is applied to organizations, they have reported a consistent increase in their profits, while they have adjusted in real time or at least reacted effectively in a very short time to changing market conditions and expectations of customers.

Software development methodologies:
As companies prepare for rapid response and customer satisfaction, we can discover some of the most important software development methodologies / models that are currently being applied in different organizations, along with their advantages and disadvantages:

Waterfall – Waterfall model focuses primarily on creating a good project plan for the software development process with a linear flow with a specific set of actions for users and that further software development of a function is made progressive after completion of the previous one. Software development based on this model is incompatible with the changing requirements and therefore the decreasing popularity.

Agile – Agile software development is the most popular framework for software engineering projects. It is a methodology that helps to align digital transformation initiatives with business needs. Because digital transformation is a continuous process, agile often helps to deliver valuable results for the company instead of waiting for a long lead time as observed in traditional software development projects.
Extreme programming (XP) – Although it is similar to the Agile framework, XP takes more time and staff compared to the other approaches. XP is mainly used when the functions of the product for software development requirements are not clear, while it ensures greater traceability within the modeling procedure, it is perfect for complicated software development projects.

Minimum Viable Product (MVP) – It is a product with exactly enough fun

The world is changing rapidly thanks to the digitization of various industries. Digitization has helped various industries upgrade rapidly by making it transparent for all the stakeholders involved.Now buyers and sellers can take a more informed decision in less time which has improved their decision making.That’s what the main advantage of digitization is, “the Transparency”. Isn’t it? But, digitization has not been yet implemented for all the industries properly. The Real estate industry is one of them. Digitization of the Real Estate Sector is still in the nascent stage. As per the ING Survey, based on 24,000 respondents, only 2% of consumers signed their purchase or rental contract digitally. And that’s what PropTechs are working on. They are working on digitizing all the relevant information so that real estate deals are done in less time and the number of digital transactions is also increased.So what all information you think can be digitized? Gone are the days when you were required to physically go to a location to have a look at the premises. Now virtual tours enabled by Virtual Reality are making it possible to have a complete picture of the premises.If you ever bought a property, were you not concerned about the true value of the property?Big data solves these issues for you through which the value of buildings can be better determined.Building Information Modelling (BIM) will improve the quality of housing projects, which will increase the trust between buyer and seller which will eventually help increase the number of real estate transactions.Sensors can help in more optimized usage of the premises and better energy performance. Blockchain, which ensures that data is not compromised, can dramatically reduce the potential for fraud by improving the transparency of data.Augmented Reality can help you visualize what your empty house would look like once you put the stuff inside. Isn’t it great?All these breakthrough technologies will be really helpful for all the stakeholders to make better and faster decisions, which will ultimately increase the overall size of the real estate industry.That’s the reason PropTechs are getting funded heavily across the world. Investments in PropTechs have increased tenfold this decade and is expected to increase further in the coming years.Eastern Enterprise has been a technology partner for many of these PropTechs and helped them in their digitization milestones.

Cunio

Cunio partnered with Eastern Enterprise to introduce a brand new property platform that connects tenants, landlords, service providers and property managers all in one tool.The Challenge they wanted to address was related to issues which tenants and landlords face on daily basis.Tenants face problems like reporting a recurring piping problem, tracking packages or receiving emergency information that would disrupt their day.Isn’t that great for tenants if someone addresses these issues?On the other hand, landlords have to deal with another set of problems like tracking said faulty pipes, tracking undelivered packages and pushing emergency notifications that would disrupt the lives of their tenants.Eastern Enterprise decided to build a MVP (Minimum Viable Product) which could be market-tested quickly followed by additional features being built over that.As the end result of this technical collaboration, Cunio was able to put itself at the forefront of real estate market with cutting edge PropTech, developed and implemented by Eastern Enterprise.You can read a detailed Case Study on Cunio here.

Direct Wonen

Direct Wonen – a leading online Property and Financial Services provider in the Dutch market partnered with Eastern Enterprise to create an online platform for tenants landlords.To serve the tenants and landlords, they tried to create an online database that posed many operational issues in terms of money and time.To solve these issues, they approached Eastern Enterprise.Eastern Enterprise received a built-in application from Direct Wonen and enhanced its functionalities.Eastern Enterprise integrated the following features for them:

  • In-app purchase capability and auto-renewal for mobile user subscriptions.
  • Third party advert API provider integration tools.
  • Responsive contract generator design for the application.
  • Application deployment and server management.
  • Implemented GDPR compliance with Social Media Integration.

Detailed Case Study on Direct Wonen can be read here.

W/E Consultants

W/E sustainable building consultants are a leader in sustainable advice for almost four decades and support organizations in their construction process from the vision stage to implementation and maintenance.W/E wanted to develop an application (GPR Vastgoed) where users/organizations can manage the sustainability performance of their buildings. They could also compare particular buildings with others using tools like maps, charts and tables.The application would also give housing corporations insight on how they could become carbon neutral by the year 2050.This novel idea would allow the end-user to build multiple roadmaps which would help them check what steps they needed to take to make their buildings more energy efficient and put them on the road to carbon neutrality.To provide the right solution, Eastern Enterprise handled a lot of complex grids and worked as a virtual team with W/E in GPR Vastgoed and used Agile SCRUM to develop this application with the expertise of both Eastern Enterprise and W/E teams.You can read the in-depth Case Study on W/E here.

Are you working on any such solution for the real estate industry?

We can help you build it or optimize it.

Get back to us for experiencing our services through “3 Day’s Tech Challenge”.

Choosing the right Javascript framework can be the single most important decision while building your web applications. While there are several Javascript framework options available Viz., Vue.JS, Meteor.JS, Ember.JS, etc., two specific names stand out and continue to be the leading frameworks in the industry Viz., Angular and React.JS. In the following sections we’ll explore the two frameworks further. Few things to consider before making this critical product development and investment decision are:

  • Code/Module Stability
  • Performance
  • Package Ecosystem
  • Community Support
  • Learning Curve
  • Documentation Overhead
  • Industry Track Record
  • Team/Maturity
  • Framework Compatibility

Angular:

Angular (also referred as “Angular 2+” or “Angular v2 and above”) is a TypeScript-based open-source web application framework. It was created by the Angular Team at Google and gained widespread support from developer community. Angular 7 is a complete rewrite from the same team that built AngularJS.

Angular is a very powerful framework and rivals React as one of the top two JavaScript frameworks. Angular has evolved through years of development behind it since 2009.

Why Angular?

  • Angular uses TypeScript, which is a superset of JavaScript that can compile down to vanilla JS. This happens to be be one of its biggest selling points.
  • Due to pre-rendering of content on the server it allows for better SEO results as well as faster browsing experience
  • The Angular framework is quite advanced technologically and is built on years of experience since the first version of Angular (2009)
  • Angular is packed with useful features such as dependency injection, templates, forms, and more.
  • Because Angular is developed and maintained by Google, users can feel confident that it will be around and used for a long while
  • The latest version is Angular 7, which was released in October 2018 and with improved performance, Angular has earned lot of praise and widespread adoption across industry
  • Angular framework is a very attractive option for young entrepreneurs building an internet startup as it it very assuring to use the tools and strategies created and recommended by the company which is perhaps the biggest.
  • Angular is a full-fledged MVC framework and React is merely a JavaScript Library i.e., just the view.
  • Angular is a very evolved and matured amongst all the Javascript frameworks with lot of safeguards. Angular has earned good support from contributors and is a complete package.
  • Angular 7 is particularly modelled for companies with large teams and developers who already use TypeScript.

React.JS:

It was developed by Facebook in 2011 and was later deployed on Instagram.com in 2012. It was open-sourced at JSConf US in May 2013. Being developed by Facebook gives lot of confidence for Developers while considering new project and it offers a sense of stability for the development process that many new frameworks just can’t.

Why React.JS?

  • As Facebook maintains the library, developers can be assured of its long term relevance
  • Due to high volume of adoption and continued growth its easier to find competent React developers
  • The adoption of JSX allows for the structuring of components that will then compile into JS React, when running on the server it enables for more SEO friendly web pages than other JS frameworks
  • React Native provides a seamless mobile experience to pair alongside your React application for the web
  • React is easy to adopt – when compared to React, Angular framework has a steep learning curve and takes lot of development maturity to get a good handle over it.
  • React is more flexible and customizable – Angular is considered a framework and it is strongly opinionated as to how your application should be structured. It also has much more “out-of-the-box” functionality. Developers don’t need to decide which routing libraries to use or other such considerations just start coding. However, Angular offers less flexibility when compared to React.
  • React.JS allows ability to integrate with other frameworks and is a great advantage for some who would like some flexibility with their code.

Conclusion:

When you consider the inherent security risks along with lot of limitations posed by React.JS as it is not a full-fledged framework, most of the major investment decisions lean towards adopting Angular. For a product based organization, Angular framework assures long term viability and scaling opportunities and hence preferred as its primary development tool/framework.

Since the advent of Human Civilization, we are finding ways of making human life better.
We started with farming, then built machines, did industrial revolution and did hundreds and thousands of other innovations/inventions to improve as a race.
Now we are heading for another revolution which would completely change the face of human life.

AI (Artificial Intelligence) would make our life easier as it’s able to develop intelligence like humans.

But, why are we developing something which would match our intelligence?

There are many simple and complex tasks which we need to do on regular basis. If we could employ a machine for doing those tasks, we can save time for doing other crucial tasks or live a better quality of life.

AI can also be used to reduce human efforts in various industries and perform the error-free
industrial tasks in a more efficient manner in lesser time.

 

AI is already touching our lives in many areas:

Real Estate
Skyline, an Israeli startup, developed an AI-based platform which can tell real estate investors what properties offer the best return. And for doing so it takes into account over
10,000 different attributes on each property.

Blok, a Finnish startup, processes housing data to estimate the price of the property based on the age of the property and its amenities.

OJO Labs uses natural language processing to provide customer service on behalf of the real estate agent.

Banking and Financial Systems
Many of the activities in the banking and financial industry are prone to human error because they take a lot of time and efforts of the employees.
Some of the activities that banks and financial institutions handle are financial operations, investing money in stock, managing various properties etc.
With the usage o AI in the process, institutions are able to achieve efficient results in lesser turnaround time.

Medical Science
AI is being used to achieve great value in medical science.
Health Care involves a lot of data. AI is able to compile & analyze lots of data and take meaningful decisions.

Analysis of tests, X-Rays, CT Scans can be done in a fraction of seconds using AI.

Drug creation can be done in lesser time using AI compared to what used to take through the normal R & D process of drugs.

‘Babylon AI doctor app’ uses speech recognition to consult with patients, checks their symptoms against a database, and offers them the best treatment.

There are immense possibilities in Medical Science through AI.

Retail / E-Commerce
Artificial Intelligence is being widely used in Retail.
Conversation intelligence software do help companies interact with the customers and do follow up with the leads by analyzing and segmenting sales calls using speech recognition
and natural language processing.

Machine Learning and predictive analytics are used in AI-based systems to provide personalized recommendations to each customer. Companies like Amazon are using these
systems which boost their revenue by impressive rates.

Now artificial neural networks are being used to model price expectations at different locations which enable retailers to offer geo-targeted discounts.

Heavy Industries
Artificial Intelligence is used in the production unit of most of the big manufacturing companies.
AI systems are used for giving specific shape to objects, test the dimensions, move objects from one place to other. And all this in a lesser amount of time.

Like all these examples of usage of AI in various industries, there are hundreds of other developments happening in AI for various other industries and ecosystems.
As it has the capability to make our lives better, AI is something which has become the next big thing.

A huge amount of data is being created for advancing in the field. With the advancement of computers and processing speed, we will be able to make sense out of this huge data
quickly.

Because of the capabilities of AI, tech giants and venture capitalists are flooding the ecosystem with huge money and infusing the market with new applications.

The Day is not far when AI will become a little less artificial and a lot more intelligent.

Do you want to contribute to AI ecosystem? Reach out to us for any queries.