Category: Custom software

According to The Wall Street Journal, consumer spending is the primary driver of economic growth in the U.S. Manufacturers, suppliers and logistics companies are the industries that benefit from retail profits. Retailers now prefer artificial intelligence to protect profits. This improves customer service as well!

Next-Gen Solutions To Solve Retail Profit Shrinkage – Why Would You Choose AritificiaI Intelligence?

In the year 2018, the global AI market was expected to be worth 7,35 billion U.S. dollars. Also, the global AI market is expected to grow from 150 percent from 2016 numbers, reaching a forecast size of 4.8 billion U.S. dollars. These statistics show that AI is a new factor of production that can help skyrocket profitability for retailers!

Related Reading: Check out the latest trends in AI. Find 7 reasons why AI is expected to play out in 2019.

Why would you choose AI to protect retail profits?

By 2035, AI technologies will have the potential to boost productivity by 40% or even more! This means AI will increase economic growth at an average of 1.7% across 16 industries by this period.

These numbers show a straight 59% increase in retail profits alone! For this, advanced analytics are used to design and develop models. These models are then used to fetch possible outcomes from a wide spectrum of data given to a computer to analyze. From these outcomes, future decisions and actions are fed to the system which learns it. The system can now perform without human intervention! It can make decisions in real-time.

Machine learning, deep learning, and natural language processing are a few examples of AI. Marketing, pricing, logistics, risk management, store management, fraud detection are some inevitable areas where the largest retailers have used AI for decades now!!

AI – How it uses advanced analytics to solve a wide spectrum of retail problems

Manufacturers, Logistics companies, and suppliers are the major industries that support retail sales. Consumer spending depends on fluctuation in these sectors. This drives the economic growth in the U.S! Since these sectors benefit from strong retail profits, “retailers are turning to artificial intelligence to help protect profits” says a report from Forbes!

AI replaces redundant and individual-driven analysis. This is a more convenient method and ensures consistency across the retail chain. Thus AI can replace 1000 people performing the same tasks by answering spontaneously with just the same analysis!

AI can also enhance customer experience and drive sales. Online retailers use chatbots and product suggestions, while stores can enjoy real-time, targeted marketing messages. Retailers have the need to generate chunks of data on a daily basis. With predictive analytics, this data can predict trends and thus reduce the chance of failures by determining necessary changes to improve profitability. Thus the employees can have proper information faster and deliver more consistent results!

Related Reading: AI and Robotics carry the power to enhance customer experience. Here’s a CTO Guide to it.

Solving Retail Problems With AI – Steps to Overcome Challenges And Improve Efficiency To Boost Sales

All retail companies (physical and online), face four fundamental challenges. These can be solved with predictive analytics and an effective data production plan. They include:

• Siloed and Static Customer Views

Retailers can adopt a complete, real-time strategy by combining traditional data sources with the non-traditional like social media or other external data sources to create valuable insight, resulting in robust fraud detection systems, more effective marketing campaigns, more accurate and targeted churn prediction, and better customer service. This helps them encounter the problems faced by siloed data, where transaction data are separated from web pages, which is again separate from CRM data.

• Time Consuming Vendor and Supply Chain Management

Retailers can adopt real-time analytics and unstructured data sets to combine structured and unstructured data to create more accurate forecasts or automatic reordering, resulting in optimized pricing strategies and more efficient inventory management.

• Analysis Based on Historical Data

Retailers can use prediction and machine learning in real time to create predictions based on current behaviors and trends. This helps them predict the client’s next move. Thus AI helps to adapt automatically to customer behaviors.

• Single-Time Data Projects

It is high time retailers turned towards automated and scalable data workflows. This helps them improve their overall efficiency. This is made possible with predictive analytics using AI.

Related Reading: Enrich customer experience at your retail store. Read along to reveal five secret to win your retail customers.

How AI can Generate Additional Revenue

IDC analysts predict that by 2019, 40 percent of retailers will have developed a customer experience architecture supported by an AI layer! In a nutshell, the major ways in which AI can generate additional revenue and help avoid additional overheads and losses are the following:

• AI can replace redundant and individual-driven analysis for a retailer. This process is far more efficient and it ensures consistency across the retailer’s stores.
• Additionally, employee theft and paperwork errors contribute a high figure of shrink to retail profits. For instance, the National Retail Federation conducted a survey and it turned out that the reason for more than 50% of retail shrink, ie, (the difference between the real ‘on-hand’ inventory and the inventory level recorded in the computer system) is a result of employee theft and manual errors! AI models yield better and efficient results.
• Also, retailers can use AI to predict solutions benefits and functionalities prior to buying it. This way, AI can help reduce risks in retail profit shrinking.
• Choosing a consultant that can address the needs of your company can be another major benefit to reap out of AI to reduce retail profit risks. The following concerns can be addressed with the consultant:

1. How to address constraints like budget, time and personnel? Ask your consultant to provide explanations for the outcomes.
2. Consider the consultant’s skill sets from their previous projects and work experience before you decide to hand over the responsibilities and contract

Related Reading: Does AI have the potential to drive business value across industries? Read through to find how AI is revolutionizing various industries.

AI adopts next-generation solutions that use predictive analytics to capitalize on their data and knowing that 80% of this data is untapped and unstructured is the winning solution! Want to know more reasons why you can undoubtedly bet your company on AI?

Stay tuned to our latest articles and blogs to learn how AI solutions have managed to perform a quantum shift in computing and revenue generation for successful retail companies!

While most sectors have battled their respective digital disruption by enhancing their own digital capabilities, the real estate sector has been considerably slow to react. This is rather astonishing when you look at the size of the real estate business globally where it surpasses all other sectors to form the most valuable commodity valued at over $217 trillion.  In the digital era, no industry is safe from disruptions and this includes the real estate sector as well.

How will custom software transform the real estate business?

With the overwhelming majority of today’s buyers belonging to the millennial group, the sector is witnessing an increased demand for digital innovation. From finance to aesthetics, there is a wide range of applications for technology in the real estate sector and this includes both commercial and residential assets.

What drives the need for digital in the real estate sector?

The three main driving forces behind digital adoption in the real estate sector are

• Buyer Experience
• Transparency
• Compliance

The buyer experience is the ultimate selling point for any property today be it commercial or residential. From the discovery of the property to guaranteed maintenance operations after a sale, today’s buyers need seamless services on all fronts. This could be made possible through a highly connected digital ecosystem that is spread across the entire buyer journey. There is a need for bringing a mature and trustworthy operational model for real estate dealings. Custom digital software can help bridge the gap between realtors, property managers, landlords and tenants in a multitude of ways and bring about transparency and accountability in matters where large financial transactions are involved. Besides the real estate sector draws quite a big eye from the authorities and compliance standards for safety which are amongst the toughest of all sectors. With a digital backbone, it becomes easier for compliance requirements to be validated and audited by government agencies. For buyers, this provides peace of mind and a hassle-free tenure with all risk aspects sorted, at both individual and government level.

What can digital transformation do for the real estate sector?

Now that you are well aware of the need to drive digital innovations, it is time to have a look at ways in which digital transformation can reshape the real estate sector. A gamut of technology innovations exists today that can deep dive into the various nuances in the sector and create lasting experiences for buyers and tenants and transform properties into global commodities. Let us examine the top 5 ways in which the real estate sector can transform with custom software.

Discovery of properties

In the 1980s, close to 22% of home buyers relied on newspaper ads and 8% relied on their friends to discover new properties to buy. In 2017, more than 51% relied on the internet to make a property or a home purchase decision. The internet has become the hotbed for real estate marketing and if you are not out online with full guns blazing, chances are that your listed property or home may not attract any potential interest from the buyers of today. Real estate developers and sellers need to have an attractive website for their property in addition to maintaining a sizable listing on the most popular property portals amongst buyers. Doing your homework on SEO and taking steps to include feedback from powerful search analytical tools provided by search engines like Google themselves, you can improve the online presence of your property considerably.

Related Reading: A Property Management Software can be a boon for real estate managers if adopted the right one. Find the secrets of finding the right property management software here.

Changing the role of real estate agents

Most digital disruptions have focused on massively reshaping the roles of personnel involved and here too, the picture is not different. With the rise of digital portals and custom software, buyers and sellers can connect more directly without losing a hefty price in terms of commissions. But agents are not completely left out as well. They, on the other hand, have a plethora of marketing and customer service tools to offer more privileged and customized services for buyers. The transformation can, however, be a bit painful for real estate agents dealing with residential properties as they can be choked out by a large number of digital listing portals wherein sellers can directly provide information, arrange site visits and even proceed with legal documentation without the agent’s help.

Transforming site visits

By the year 2025, nearly 20 million households in the US would be owned exclusively by folks in the millennial generation. If you expect them to drop by after work or on a Sunday for a property visit, then chances are you will never hear from them after the first inquiry. In the digital age, you can use custom software to schedule and arrange for a suitable site visit time slot that is favorable for both the potential buyer and the agent. It can even facilitate pre-visit conditions such as a deposit, online application, valid document proof, etc. Going a step further, virtual and augmented reality embedded apps can provide a 360-degree walk-through of the property on the buyer’s mobile phone anytime and anywhere. With such digital innovations, the target market would not hesitate in spending an extra premium thanks to the splendid buying experience.

Related Reading: Self Showing App, an IoT application built by Fingent streamlines the complete inspection and leasing procedures of real estate firms. Find more in the case study here.

Setting the terms of leasing or buying

Gone are the days, when you needed hours of documentation to create a transparent lease or buying agreement that aligns with regional laws and complies with all relevant risk management standards. Today custom real estate software can provide digital lease or buying agreements that can be validated by local, regional or national government authorities directly without middlemen leading to significant cost reduction in the entire process. A digital portal could record every transaction from the first site visit pre-requisites to valid document audits, payment information, terms and conditions of the agreement including periodic rental revision agreements, automated payment schedules, etc. Such a massive transformation can bring about significant changes to both residential and commercial real estate properties.

Preventing fraudulent transactions

Having a digital backbone brings with it guaranteed transparency and accountability for every transaction or commitment made between a buyer and a seller. Besides, digital portals having direct validation credentials with government authorities can provide digital verification of documents, identity proofs and other associated legal requirements for every transaction. This can aid in transparent pricing schemes, elimination of bribes and middlemen fees, provide streamlined tax revenue to governments for every deal in the real estate sector thereby eliminating fraudulent transactions.

Related Reading: Read through the case study to know how Fingent developed a customized all-in-one property management solution for one of their leading real estate client here.

Summing up

Though much of the transformation mentioned above is in various initial stages, the real estate sector holds immense potential for future digital innovation. Custom software for the real estate sector can challenge traditional buyer-seller relationships and even wipe out middlemen in the long run as we mentioned in one of the possibilities above. However, staying ahead and relevant at the same time in the digital era is what key players in the sector need to focus their attention on. Write to us to know how our digital transformation specialists can enable the best of real estate innovations for you.  

The real estate industry has traditionally been a technology laggard, with antiquated systems, ad-hoc processes and manual documentation ruling the roost. However, things are changing, with innovation and tech disruption set to change the fundamental paradigms of the real estate sector.

Can real estate technology advances actually predict property prices?

Leveraging Machine Learning Algorithms to Predict Real Estate Property Prices

Smart purchasers and investors look at the value of the property rather than the price. Just as the price of a stock denotes nothing about its inherent value, and one needs to delve into the PE and other ratios to estimate the value of the stock, the price of a property says little about its actual worth, and one has to dig into the underlying data to get to the true worth of a property.

The opacity and lack of access to underlying information surrounding property hitherto inhibited a proper and objective analysis of the true worth of property. Often, the only information available to the stakeholders is the prices at which previous properties of a similar nature, in the same locality were sold. As such, the asking price for properties has always been subjective, depending on what the seller thinks the property is worth, with a loose estimate of the prices other properties have sold in the locality and other subjective insights constituting the basis for asking price.

However, things are changing, and changing fast. Real estate data sets are growing larger and larger with every passing day, every single day, thanks to the ever-improving computing power and cloud storage capabilities.  Smart retailers and other stakeholders have already deployed several new tools and services that leverage such data, and many more tools and services are in the offing.

The National Association of Realtors estimates about 42% of buyers looking at property online as the first step in their home buying process. Most of them now delve into further details, such as the crime rates in the neighborhood, availability of public transit, the profile of local businesses such as gyms, groceries, restaurants, and several other factors.

It gets better. Machine learning now infuses objectivity and transparency in property pricing, besides promising a scientific basis into price fixation of property.

Machine learning models, comprising of hundreds of explanatory variables, offer insights into almost every aspect of a specific property, to a very a high level of accuracy and objectivity. Such models scour through piles of data and are capable of not just identifying an accurate price for the property, but also identifying hidden gems among the swathes of properties available for sale. Buyers and may use such insights to quote a fair and accurate price for the property, Sellers may likewise quote a fair price and sell their property faster, without the risk of under-selling themselves. Banks and financial institutions may use the insights to offer loans based on the predicted future value.

Related Reading: How Top Real Estate Companies Leverage Technology to Soar New Heights.

Identifying Correlated Variables

Home buyers and investors often end up making unscientific comparison among two properties and are often deluded by a lesser price for a property, oblivious to the far inferior value on offer.

While the obvious variables such as the number of bedrooms and square foot area may be obvious and explicit, some variables remain hidden or not too obvious.

Some variables are also closely correlated with others. Some pairs, correlated by nature, such as “Basement finished area” and “Basement unfinished Area,” and other pairs, correlated by deduction, such as “Overall condition” and “Year built” help to identify the true worth of a property relative to the asking price.

Machine learning models not only factor in such variables but also give proper weight to each variable. For instance, two homes may seem similar while considering the obvious variables, but property A may offer far better value owing to the superior quality of plumbing materials used in construction and availability of groundwater compared to property B.

Related Reading: Find how Fingent developed a customized solution to streamline all the processes in a property management life cycle. Check out the case study – Rentmoji: All-In-One Property Management Platform.

Unearthing Seasonal factors

Seasonality has an impact on property prices, but the impact may be subtle or hidden. Crunching historical data makes explicit trends in sales prices associated with seasons. For instance, sales may be more surfing summer months, when the new school year starts, leading to a spike in prices. Such seasonal prices help property investors leverage their buys, property sellers price their property more accurately, or postpone their sell for a few months to get a better price, and more.

Related Infographic: Major Challenges of Big Data in The Real Estate Industry

Identifying the True Value of Extraneous Factors

Buyers always consider the neighborhood of the property, in terms of crime rates, the quality of grocery shops in the vicinity, the proximity of schools, and other factors. However, such analysis is often done ad-hoc, and on a generic basis. The “devil” in the detail may often be overlooked. Machine learning models factor in the extraneous factors at a much deeper level, correlating factors such as frequency of power cuts in the locality, unemployment in the locality, frequency of transportation links, school ratings and more, all of which not only offer an objective and scientific basis on the true worth of the property, but also have an immediate bearing on the property prices.

However, the true value of machine learning is the ability to derive valuable trends and insights from the data. For instance, analysis of police arrests and the chemical compounds in sewers indicate the use of crack cocaine, indicating that gentrification could soon arrive. When the crack is replaced by cocaine, it may indicate that gentrification may already be complete. Such insights may not be available at plain sight and may be impossible to decipher without the analysis of such underlying data.

While real estate technology now makes it easy to predict property prices with a high level of accuracy and objectivity, the challenge is creating the underlying data models in a robust way. The machine learning system is only as good as the algorithm which powers it. Success depends on creating linear models, co-opting all possible categorical variables and historical data associated with each variable.

Related Reading: Read through to find how trending technology is disrupting the real estate industry.

The digital transformation wave that is transforming businesses across the world has had major influences on the way custom software development is treated by technology teams. Today software development is all about improving the experiences at multiple levels for businesses. Experiences include customer experiences from their end customers during a transaction journey and operational experience of staff who utilize technology solutions to drive more customer love. Technology is bound to change and business owners must be willing to meaningfully bring about changes in their custom software development concepts to incorporate the best solutions to run their business smoothly.

Reap your success in the digital age following these 5 custom software development trends

Let’s have a look at the changing trends in custom software development that warrants big attention from businesses across sectors. Following are our picks of the top 5 contenders in technology trends that every team engaged in custom software development must be aware of:

1. The growth of open source technology

A decade ago, you might not have found too many takers for open source technology. But, today only less than 3% of worldwide businesses do not use any form of open source software in their enterprise technology stack. In the initial days, it was largely seen as a playground for beginners in software development to try out building applications for free. Today the world’s biggest technology companies like Google and Facebook utilize open source software to run their most mission-critical systems. They also contribute significantly to the maintenance and growth of developer communities around these open source technologies. Take a look at all the leading application development technology available today like Java, PHP, Angular, React, Hadoop, etc. They are all open source and powers some of the world’s biggest enterprise and consumer-facing digital applications. If your business has frequent technology requirements, then this is a trend in custom software development that definitely needs to be on your top priority.

2. AI-ready software

AI is already a mainstream component of almost every digital platform that people use today. From e-commerce to movie streaming, companies are rolling out machine learning capability to help software learn more about its users and automatically provide them with great experiences. AI-powered chatbots are today serving queries of billions of people online and businesses are investing heavily in making these bots more intelligent by the minute. For software developers, it is essential to know the in and out of writing code that blends well with self-learning algorithms to provide optimal value for businesses utilizing applications that run this code. AI has a key role to play in the future when it comes to interacting with end customers directly. Hence custom software developers need to focus their skills on creating meaningful front-ends that can resonate AI actions, scalable back end engineering that can supplement complex AI algorithms and powerful databases that can deal with the huge volume of data that needs to be handled by AI systems to create meaningful experiences.

Related Reading: Find the top AI trends of 2019.

3. Cloud takes new dimensions

The world’s best run businesses today run their technology core on the cloud. From platforms to infrastructure, cloud computing has transformed the way enterprises use software applications. 73 % of the world’s businesses have at least one application or an infrastructure element on the cloud. From becoming more agile in terms of application engineering to saving fortunes by removing on-premise infrastructure costs, businesses are re-inventing themselves in the digital age. The benefits are endless – scalability on demand, global availability, top gun service providers in every niche, etc. With cloud computing, your technology workforce can be empowered with mobility i.e. the freedom to work wherever they want and with whatever resources they need. This is yet another trend that every business needs to take seriously to improve their ROI on technology investments.

Related Reading: Find how a cloud platform like INFINCE can untangle technology for business.

4. Security to be given a top priority

While the rise of cloud computing and the transition of on-premise software engineering to rich internet applications have created better digital experiences, they have opened new cans of worms for developers to deal with. In the US alone it was reported that there are over 130 large scale targeted breaches of confidential user data residing on enterprise applications of businesses. This figure is growing at an exponential rate of 27% every year as well. Security aspects cannot be overlooked now not even for the smallest of applications. Any vulnerability in your code will turn into a feasting ground for cyber threats in an increasingly internet dominated world. It’s not enough to write a great code but also to practice secure coding standards to enhance safety and ensure customer data is never compromised.

Related Reading: Find which option is a better choice for your business, Custom Software or Off-the-shelf.

5. Customers are the heart of everything

Today it is not just your sales process or your customer relations team that needs to have end-consumer centric thinking on their operations. Even your custom software development team needs to have a work objective centered on a customer-first philosophy. Human behavior of your target digital audience needs to be modeled and referred to while creating applications. This is crucial for recommendation systems, lasting user experiences and above all improve brand loyalty by creating wonderful digital experiences. Feedback systems need to convey responses directly to core technology teams and they need to drill this feedback into the very depths of every implementation and every programming logic they use to achieve business goals.

These are our picks for the top 5 trends in custom software development that businesses of all sizes need to consider today. In an increasingly digital age where customers dictate the fate of every single of your investment, it is imperative for organizations to have a comprehensive look at how these trends can be incorporated into their technology roadmaps. Those failing to do so are in for massive repercussions as it doesn’t take decades for big corporations to fall to their heels for lack of innovation. The examples are right in front of you. Investing in the right technology with the right advisory is crucial for businesses to continuously innovate and stay relevant in changing times.

Most of us, technology geeks or not, are eager to stay first in line to catch up with the latest game-changing technology trends. Here we are to know which technologies will thrive in future!

The Potential Technology Trends You Need To Explore In 2025

Have you ever looked up at the sky and clapped your eyelids on a bat? This is commonplace. But what if it was a drone. Or would it be a flying fleet? Since we don’t belong to the Jetsons family, the latter is not expected but we are close to it! This year is definitely a transformative year for technological innovation!

According to Gartner, the Top 10 Strategic Technology Trends for coming years are Block chain, Artificial Intelligence, Empowered Edge, Privacy and Digital Ethics, Quantum Computing, Immersive Experiences, Augmented Analytics, Autonomous Things, and Digital Twins!

This is just the tip of the iceberg. Following are the emerging technology trends and catalyzing technical innovation that we can expect to see more of in future!!

Related Reading: Find how digital innovation is transforming today’s business world.

1. Blockchain Technology – The ‘New Internet’

Some call Blockchain technology the ‘New Internet’. The blockchain is the brainchild of a person or group of people known by the pseudonym, Satoshi Nakamoto. It permits digital information to be distributed but not duplicated.

It was first devised for the digital currency, Bitcoin.  It is also called the “digital gold”. To this day, the total value of the currency is nearly $112 billion US!

“Blockchain solves the manipulation problem”, says Vitalik Buterin, inventor of Ethereum.

2. Artificial Intelligence (AI)

Apart from AI-powered chatbots, This year will witness chip manufacturers such as Intel, NVIDIA, AMD, ARM, and Qualcomm shipping specialized chips that speed up the execution of AI-enabled applications.

This year will also be the year for hyperscale infrastructure companies like Amazon, Microsoft, Google, and Facebook.

Related Reading: Check out the top AI trends

3. Cloud-independent edge computing

The study from IDC illustrates that 45 percent of the entire data created by IoT devices will be stored, processed, analyzed and acted upon close to or at the edge of a network by 2024! Edge computing is a mesh network of data centers that process and store data locally before being sent to a centralized storage center or cloud.

4. Privacy and Digital Ethics

Facebook, recently witnessed the biggest security breach in which 50 million accounts were compromised. Facebook, later clarified that data of 30 million accounts were stolen.

People are becoming more nervous about how organizations and third-parties are using their personal data.

5. Quantum Computing

The world is behind building the first fully-functional quantum computer. Also called the supercomputer, this is expected to be a cloud service rather than an on-prem service. IBM is already offering cloud-based quantum computing services. For instance, the automotive, financial, insurance, pharmaceuticals, military, and research industries have the most to gain from the advancements in Quantum Computing.

6. Immersive Experiences

Conversational platforms are changing the way in which people communicate with the digital world. Virtual reality (VR), augmented reality (AR) and mixed reality (MR) are changing their approaches to know more about people’s perception.

7. Augmented Analytics

Augmented analytics relies on augmented intelligence. This uses machine learning (ML) to transform how analytics content can be developed, consumed and shared.

“Through 2020, the number of data scientists will grow five times faster than the number of experts”, says David Cearley!

8. Autonomous Things

Autonomous things, such as robots, drones, and autonomous fleet, use Artificial Intelligence techniques to automate their functions that were previously performed by humans.

9. Digital Twins

A digital twin is a digital representation of real-world items that are interlinked. Cearley states that there can be digital twins of people, processes, and things!

A DTO is an aspect of the Digital Twin evolution that is a dynamic software model that relies on operational or other data. DTOs help drive efficiencies in business processes.

Apart from these, there are other key technology trends that organizations need to explore in future. These include:

10. Cybersecurity and Risk Management

According to the estimates from the firm Gemalto, the data breaches were 4.5 billion in the first half of 2018! The University of Maryland study found that hackers attack computers every 39 seconds.

In coming years we will be facing a more sophisticated array of physical security and cybersecurity challenges.

Cybersecurity is thus the digital glue that has held IoT, Smart Cities, and the world of converged machines, sensors, applications, and algorithms operational throughout!

11. Smart Spaces

A smart space is a physical or digital environment in which humans and technology-enabled systems interact in an increasingly open, connected, coordinated and intelligent ecosystems, according to Gartner! The world of technology is to enter accelerated delivery of smart spaces in 2019.

 12. Self-powered data centers

Data centers grow every minute with the implementation of virtual servers and storage, energy-efficient buildings. In coming years, the data centers are expected to run on its own self-contained power plants!

13. IoT integration

This year will witness more IoT implementation. An International Forrester IT survey that said among a recent group study, 82% of respondents were unable to identify all of the devices connected to their networks. Of this lot, 54% were nervous about device security, and 55% were concerned about integration!

Related Reading: Find the role of Data Analytics in Internet of Things (IoT)

14. More self-service IT kiosks for business users

This year will be a year of IT innovation designed to build better communication between IT and end users. The self-service IT kiosks to be set up would enable users to log on and choose what they want for the apps that they build.

15. The Internet of Things and Smart Cities

50 billion equipment, including smartphones, and others are expected by the IoT to be wirelessly connected via a network of sensors to the internetin future. 

The term “Smart City” means creating a public/private infrastructure to conduct activities that protect and secure citizens. It integrates communications (5-G), transportation, energy, water resources, waste collections, smart-building technologies, and security technologies and services!

To upgrade your business with the latest technology trends on the table, contact the experts at Fingent today! Also, read through our latest blogs to learn more about accelerated technological development!!

The Experts Speak: The Adoption of AI and ML in Software Development

Artificial Intelligence (AI) and Machine Learning (ML) is transforming nearly every industry. In our previous blogs, we discussed how it is transforming finance, customer service, supply chain & logistics, and other industries. In this blog, we will talk about how AI and ML are radicalizing the software industry. We will look at the benefits of the adoption of AI and ML in software development and what industry experts have to say about it.

The Fundamental Shift in Software Development

At its very core, software development involves writing reams of rule-based code. Traditionally, developers had to specify every detail to let the system know what to do, and then customize the features of each piece of technology. With the adoption of Artificial Intelligence and Machine Learning, this process becomes much easier.

Author, scientist and Google research engineer Pete Warden puts it well:

“The pattern is that there’s an existing software project doing data processing using explicit programming logic, and the team charged with maintaining it find they can replace it with a deep-learning-based solution … What I see is that almost any data processing system with non-trivial logic can be improved significantly by applying modern machine learning. This might sound less than dramatic when put in those terms, but it’s a radical change in how we build software. Instead of writing and maintaining intricate, layered tangles of logic, the developer has to become a teacher, a curator of training data and an analyst of results.”

Practically, this means a revolutionary change in the very essence of software development.

AI and ML in action

“Modern IT environments are incredibly (and increasingly) complex and ever-changing, leading to large amounts of time and resources devoted to monitoring, troubleshooting, and course correcting,” says Phil Tee, Cofounder, and CEO of Moogsoft Inc. “It’s a reactive position for most companies, but when teams use AIOps technology they can leverage change-tolerant algorithms and access indexed information. This allows them to spend more time focused on proactive, meaningful work rather than fixing the same problems repeatedly or spending time managing rules and filters.”

Artificial Intelligence and Machine Learning can transform the entire Software Development Life Cycle (SDLC). Three ways in which it does this are:

• Synthesis of large volumes of data to predict the success or failure and business value of a project.
• Predicts accurate project delivery timelines, delivers project status updates and creates project schedules.
• Automatic diagnosis and rectification of problems in the project.

Let us consider the details of how this is achieved.

1. Turn Idea into Code Quickly and Effectively

The process from the inception of an idea to its actual execution into workable code is time-consuming and complex. Traditionally, developers must go through a long process of trial and error to get the basic code in place. Obtaining funding approvals for the project is complicated as well and requires getting the project to a prototype level even before requesting for funds. All this can be made easy with AI and ML. In the future, the system itself could learn to process ideas from natural language and suggest machine-executable code without human intervention.  AI and ML are making this possible even now by teaching systems to suggest code completion. This way systems will slowly learn to generate code through predefined modules.

Considering the viability of a project also becomes easier and faster with AI and ML. Machine learning can help developers identify and prioritize the effects of the project based on business risk. This way, time and effort on unnecessary regression testing and rectification can be eliminated. A sound decision on whether the project is feasible or not can thus be made in the earlier stages.

Related Reading: How to accelerate your business growth with Robotic Process Automation

2. Effective Project Management

Through pattern detection, AI and ML can be trained to use details of past projects to provide accurate estimates of the current project. Historical project details like bugs, test phases, actuals, and estimated values can be fed into the system and used to fine-tune the level of accuracy. Through this, the system will learn to predict accurate delivery schedules and create work schedules for individual members of the team. Risk Management, as well as Resource Management, can be better executed this way.

3. Automation of Testing and Error Detection

Pattern Detection is one of the most valued benefits of machine learning. This can be used effectively to automate the testing and debugging process in software development. One of the challenges of software testing is to come up with a list of most likely cases and scenarios that could affect the program’s performance. Through pattern detection, systems can look at past logs and generate a test case list automatically. They can also identify and classify error types and in time learn to automatically fix these errors.

Joe Colantonio, an expert on software automation and performance testing discusses what is possible with AI and ML.  “Wouldn’t it be great if you could answer the classic testing question, “If I’ve made a change in this piece of code, what’s the minimum number of tests I should be able to run in order to figure out whether or not this change is good or bad?” he says. “Many companies are using AI tools that do just that. Using ML, they can tell you with precision what the smallest number of tests is to test the piece of changed code. The tools can also analyze your current test coverage and flag areas that have little coverage, or point out areas in your application that are at risk.”

Revolutionizing IT

Apart from making a big difference in the software development process, Artificial Intelligence and Machine Learning will also change the way applications are made. With the power of AI and ML, developers will be able to design apps, which will be able to listen, think, speak, reason and make decisions. Vision Recognition technologies, Optical character recognition, and many more AI-powered capabilities will help developers create faster, smarter and better apps in the future. At Fingent, we endeavor to put this into action every day. There is no area that is immune to the changes that AI and ML can bring and we are determined to stay on top of it.

Related Reading: Top Artificial Intelligence Trends to Watch Out for In 2019

Digital revolution has not just changed how businesses are perceived but also how businesses are performed. It meant a shift from the conventional means of operation to the one aided by technology. In today’s age, every aspect of a business from operations to management is run using digital tools. Such digital transformations has changed every industry and revolutionized the way of serving the customers, improve the competitiveness of the business and pushed forth its expansion into the global market.

Coleman Parkes Research in one of their surveys identifies that 82 percent of respondents have adopted digital technologies for redefining their businesses. This complete overhaul of business with the reinvention of business operations are affected by the advent of mobile, cloud, social, and big data analytics. So has the transcendence of a digital world helped grow businesses? If yes, what are the ways in which businesses can take advantage of the same?

Related Reading: Implementing a digital transformation strategy for your business requires adequate know-how of the varied process involved in the same. Know about the five crucial questions to consider before initiating your digital transformation journey here.

What are the innovative changes?

Early on, businesses built websites as a front for providing only information. With interactivity and the onset of the mobile revolution, sites and apps started to provide much more. They are used to offer services and products right at the doorstep of customers. The use of social media has enhanced the knowledge regarding what the customers like and what they seek. Businesses can use this medium to understand and tailor personalized experiences to provide real value to their customers.

Big Data analytics has changed the way businesses adapt and change. From decision making to predicting customer preferences and hiring the right skill sets, big data analytics has emerged as the game changer for businesses today by influencing how they deal their data.  Instead of undertaking a market study, there is relevant data that tells what is working in the market and what is not.

The competitiveness

Each business that enters into a digital transformation is out there to compete every second. Imagine the new generation of customers who have everything at the tap of a button. Businesses need to be on their toes to deliver rich, real-time interactions with an element of personalization to keep their customers engaged. Also, the need to keep updating and innovating with respect to the competition is a necessity to save the business from running into the ground.

Read more: Fundraising Software For Nonprofits

The increased reach

Even though the competition increases with the digital transformation, businesses can take advantage of the fact that now they have reached a global audience. There is a market for the niche of products and services since customers have a way to access them easily. Also putting a step into innovation ensures that your business is at the forefront of achieving a profitable chunk out of the industry.

Improved avenues

Since transforming the business into a digital space is no longer an option, businesses should start utilizing the benefits of such a change. Pervasive digitization of services and products can be made to ensure that there are no barriers between the business and their customers. Also, traditional companies can start making efforts to revamp or add new services that are digitally available to increase their profits. Monetization from digital platforms and collaborations with partners can further help achieve better profits from an untapped source of customer relationships.

Related Reading: Take a look at the CIO’s opinions of digital transformation initiatives deployed across different businesses here.

How to make the most of this digital transformation?

In today’s day and age, no business is smaller or bigger, each of them competes in a virtual, digital space that offers fair ground for competition. Businesses should start looking at Big Data analytics and use the social media space to push their content to the customers. The idea is to be always supple, no matter how big or small your business is. Think like a startup at every step to understand the new technologies, the revolutionary changes, and be flexible to adopt them quickly. Having a digital core at the heart of your organization to manage and operate the business is the right way to go ahead in this modern digital era.

If your business is seeking to get into the race of digital transformation, it is important to act right now. Late adopters can have serious disadvantages since the competition is already in the domain. If you are looking to adopt a business model that utilizes a digital core, Fingent top custom software development company can help you to embrace the digital transformation with the best developers to get to the forefront of change. 

iOS 12 is now live and represents the latest evolution of Apple over its decade long existence. Today, Apple’s App Store has over two million apps with over 170 billion downloads and over $130 billion in revenue. With iOS 12, developers are poised to offer a far superior experience for users compared to previous versions.

Here are the top iOS 12 application development features that enterprises can benefit.

Siri Shortcuts Take User Experience to a New Level

Adoption of Siri is increasing at an exponential pace, considering the popularity of using voice technology for commands and simplifying user actions. True to form, iOS 12 makes Apple’s personal assistant more proactive, by allowing shortcuts.

Siri Shortcuts minimize the number of steps users take to accomplish everyday tasks. Siri intelligently pairs users’ daily routines with app functionality and suggests convenient shortcuts whenever available. Such shortcuts allow users to access the offered functionality or complete the task on hand from the lock screen or from search, without having to open the app.

Siri learns and predicts shortcuts through “donations.” Developers and users may “donate” shortcuts to Siri. Developers may use the Shortcuts API to donate the shortcuts they wish to offer their users. The prerequisite towards “donations” that meet the objectives is developers having an accurate understanding of the specific in-app actions that drive the most engagement, to make the relevant Siri Shortcut donations for the most frequently used features.

The flip side to making donations for shortcuts is handling user expectations. Users may, for instance, expect the app to have shortcuts for features where shortcuts are not technically possible. For instance, when the app requires user authentication before completing an action, such a feature cannot run in the background, as a shortcut.

Improved Core ML 2 Brings Machine Learning to Apps Easily

Core ML is a relatively new toolkit, but very critical, considering it now powers Siri, Quick Type, and Camera functions in iOS. Core ML allow developers to integrate machine learning models including text, barcode, face, and landmark detection, object tracking, enhanced image recognition, and other intuitive functionality into apps, easily. Core ML 2 comes with over 30 layer types and supports expansive deep learning capabilities. Developers may run on-device machine learning models without the need to analyze data across multiple servers.

iOS 12 makes it easy, simple and fast to integrate Core ML 2 with user-facing apps. Developers can leverage this handy toolkit to embed machine learning frameworks and models directly into mobile apps, with just a few lines of code, and with no extensive technical expertise required.

A New CreateML Framework Allow Lay Users to Create Machine Learning Models

Create ML, a new framework, allow developers to build machine learning models, with little to no machine learning expertise. Its similarity with Swift makes the framework familiar and comfortable to use. Create ML is also integrated into Xcode 10 playgrounds, making it easy to view model workflows in real time.

Developers can leverage the embedded natural language capabilities of iOS 12 to create in-depth models for advanced purposes such as regression, image classification, word tagging, and sentence classification, with just a few lines of Swift code.

Highly Intuitive ArKIT2 Toolkit Takes AR Experiences to a New Level

The improved ArKit 2 toolkit allows developers to create powerful and hugely incredible Artificial Reality (AR) immersive experiences. The toolkit enables developers to create engaging multiplayer games, presentations and more, allowing multiple users to view or play the AR enhanced simulations simultaneously. The ingenuity of the toolkit enables developers to offer users the option to save the AR experience and resume it at a later time, co-opt real-world objects into the AR experiences, and much more.

Interactive Push Notifications

iOS 12 changes the way users receive push notifications. Users now gain considerable control over the type of push notifications they choose to receive and how they receive such notification. Users gain access to message settings directly from the push notification interface, allowing them to opt-out of messages from the device’s lock screen. The enhanced downtime settings enable users to ignore push notifications entirely.

Such new functionality, however, creates a new challenge for developers. It is no longer enough to somehow coax the user to download the app. The obvious requirement to remain in the user’s scheme of thing is to provide better and highly personalized, stand-out content in the push notification. Developers can also add buttons and switches to the push notifications, to encourage user action, infusing interactivity to push notifications. Developers can also customize the font, image, and other elements of the push notification.

End of Password Annoyance with iOS 12 Application Development

iOS 12 offer developers access to Password Autofill. Users may leverage this new feature to create and save passwords, and then log in to incumbent accounts, with just a few taps, regardless of the device. The password autofill functionality saves the user’s password on the device, and users can now share the data across devices using the iCloud keychain.

The new password autofill option significantly improves the user’s onboarding process, offering the path of least resistance. Empirical evidence suggests complicated registration fields harm user acquisition efforts and increase user abandonment. Also, contrary to the first impression, the autofill option actually increases app security. Autofill suggests strong, unique passwords at the onset.

While features and options are aplenty in the new iOS 12, the key to successful app development is picking and choosing the right features, relevant for the project. A tie-up with competent professionals with a history of having developed successful apps helps.

Related Reading:  How to Empower your Business with an iOS Application

Artificial Intelligence (AI) is the rage now, but like all things tech, it is in a continuous state of evolution. Here is how Artificial Intelligence is expected to play out in 2024.

1. Complex AI-enabled chips in the Offing

The tremendous power of Artificial Intelligence, manifesting in the ability to undertake advanced mathematical calculations, number crunching, facial recognition, object detection, and other complex tasks, come with a hardware cost. Even the fastest and most advanced CPU is inadequate to improve the speed of training an AI model. Seamless execution of AI models requires additional hardware, in the form of specialized processors to complement the CPU.

Leading chip manufacturers such as AMD, Intel, NVIDIA, Qualcomm, and others, however, are working on removing the limitation, and are on the cusp of rolling out specialized chips that speed up the execution of AI-enabled applications. Hyperscale infrastructure companies such as Google, Amazon, Microsoft, and Facebook are also increasing investments in custom chip development. These new chips would be based on field programmable gate arrays (FPGA) and application specific integrated circuits (ASIC) and optimized for specific use cases and scenarios.

Needless to say, the new chips in the offing would make high-performance computing tasks such as query processing and predictive analytics very fast and seamless. Such chips would find application in a host of industries such as healthcare, automobile, and more.

Some of the early bird initiatives, such as Project Nitro from Amazon, Cloud TPUs from Google, Project Brainwave from Microsoft, Intel Myriad X VPU is a portent of the things to come in future.

2. Rise of ONNX to Facilitate Interoperability among Neural Networks

Developing workable AI based neural networks depends largely on selecting the right framework. While plenty of choices exist as to frameworks, developers are hamstrung by the lack of interoperability among such frameworks. This holds true for all the popular frameworks in vogue, including TensorFlow, Caffe2, Apache MXNet, PyTorch, Microsoft Cognitive Toolkit, and others.

Industry biggies such as AWS, Facebook and Microsoft are however are working on it, and have collaborated to build Open Neural Network Exchange (ONNX), which makes it possible to reuse trained neural network models across multiple frameworks.

ONNX is all set to become an essential technology for the industry in coming years, adopted by the stakeholders in a big way. Windows 10 ships already with ONNX runtime and Intel’s OpenVINO toolkit already supports ONNX, indicating the trend.

3. Automated Machine Learning to Gain Prominence

Machine Learning holds unbound promise but developing models is hard work, and the highly advanced expertise required stifles possibilities.

AutoML is however all set to change things. Applied the right way, it would empower business analysts and developers to evolve machine learning models capable of addressing complex scenarios without having to go through the usually arduous and vexatious process of training ML models, or going through elaborate workflows. Business analysts could focus on the business problem on hand, rather than worry about process and workflow.
AutoML offers the same level of flexibility that cognitive APIs perform, but also offer high portability and ability to co-opt custom data.

DataRobot, Google Cloud AutoML, Microsoft Custom Cognitive APIs, Custom Entities for Amazon Comprehend are some of the AutoML solutions already launched. The popularity of these tools indicates widespread popularity for AutoML in future.

4. Automation of DevOps through AIOps

AIOps represent the convergence of AI and DevOps. Such a convergence, which is all set to go mainstream, will benefit public cloud vendors and enterprises considerably.

Modern applications and infrastructure generate considerable log data, generated by hardware, server and application software, operating systems, and other sources. Such data finds a use for indexing, searching, and analytics, and is also aggregated and correlated to find insights and patterns. The application of machine learning models to such datasets makes IT operations proactive. Business managers and other stakeholders obtain insights in real time, allowing prompt and timely action. Enterprises could, for instance, leverage the improved and real-time intelligence to perform precise and accurate root cause analysis.

Some of the AIOps based tools already in vogue include Amazon EC2 Predictive Scaling, Amazon S3 Intelligent Tiering, Moogsoft AIOps, and Azure VM resiliency.

5. The rise of Virtual Agents

Businesses have started using Artificial Intelligence powered chatbots in increasing numbers. Chatbots answer questions, qualify sales leads and assist check out for online customers, among other applications. This year is likely to see an upgrade from chatbots to AI-powered virtual agents capable of handling even more complex customer service tasks, with even a face and personality of their own.

As a portent of things to come, Ava, Autodesk’s virtual agent, comes with a female face and a powerful persona that resonate the company’s brand image. Needless to say, such virtual agents are much more effective than human agents.

6. Increasing Role of Artificial Intelligence in Cyber Defense

Cybercrime has been a major issue for several years now. Cybercriminals target cloud infrastructure, IoT, and other cyber assets at will. Coming days will see an increasing application of Artificial Intelligence to fight cybercrime and keep cyber networks secure.

Artificial intelligence and machine learning are already applied to pick up subtle indicators of abnormal activities, detect online enemies in real time, and nip cyber threats in the bud.

7. AI to Power Smarter Retail Recommendations

The advancements in Artificial intelligence enable businesses and marketers to develop models that would recommend products based on not just the customer’s browsing history, but also the tone and sentiment. In future, companies will embrace AI-based solutions to offer their customers highly personalized shopping experiences. Such experiences would expand beyond e-commerce to brick and mortar stores as well, through digital interfaces.

It is interesting times ahead for AI. Smart enterprises would do well to tag tech companies who keep themselves abreast with the latest developments in this red-hot emerging technology and develop solutions to apply it to roll out workable solutions.

Related Reading : Unconventional Ways Artificial Intelligence Drives Business Value

The Healthcare sector is booming at a faster rate and the necessity to manage patient care and innovate medicines has increased synonymously. With the rise in such needs, newer technologies are being adopted in the industry. One such major change that might take place in the future is the use of Big Data and Analytics in the Healthcare sector.

According to an International Data Corporation (IDC) report sponsored by Seagate Technology, it is found that big data is projected to grow faster in healthcare than in sectors like manufacturing, financial services or media. It is estimated that the healthcare data will experience a compound annual growth rate (CAGR) of 36 percent through 2025.

Market research have shown that the global big data in the healthcare market is expected to reach $34.27 billion by 2022 at a CAGR of 22.07%. Globally, the big data analytics segment are expected to be worth more than $68.03 billion by 2024, driven largely by continued North American investments in electronic health records, practice management tools, and workforce management solutions.

Here are 5 ways in which Big Data can help and change the entire scenario of the Healthcare sector.

1. Health Tracking

Big Data and Analytics along with the Internet of Things (IoT), is revolutionizing the way one can track various user statistics and vitals. Apart from the basic wearables that can detect the patient’s sleep, heart rate, exercise, distance walked, etc. there are new medical innovations that can monitor the patient’s blood pressure, pulse Oximeters, glucose monitors, and more. The continuous monitoring of the body vitals along with the sensor data collection will allow healthcare organizations to keep people out of the hospital since they can identify potential health issue and provide care before the situation goes worse.

2. Reducing Cost

Big Data can be a great way to save costs for hospitals that either over or under book staff members. Predictive analysis can help resolve this issue by predicting the admission rates and help with staff allocation. This will reduce the Rate of Investment incurred by hospitals and in fact help utilize their investment to the max. The insurance industry can save money by backing wearables and health trackers to ensure that patients do not spend time in the hospital. It can save wait times for patients since the hospital will have adequate staff and beds available as per the analysis all the time. Predictive analytics also helps cut costs by reducing the rate of hospital readmissions.

According to a recent report by the Society of Actuaries, 47% of healthcare organizations are already using predictive analytics. It is also noted that over 57% of healthcare sectors believe that predictive analytics will save organizations 25 percent or more in annual costs over the next five years.

Healthcare & Big Data Facts: McKinsey & Company report states that after 20 years of steady increases, healthcare expenses now represent 17.6% of GDP, ie. nearly $600 billion more than the expected benchmark for the U.S. size and wealth.

3. Assisting High-Risk Patients

If all the hospital records are digitized, it will be the perfect data that can be accessed to understand the pattern of many patients. It can identify the patients approaching the hospital repeatedly and identify their chronic issues. Such understanding will help in giving such patients better care and provide an insight into corrective measures to reduce their frequent visits. It is a great way to keep a list and check on high-risk patients and offer them customized care.

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4. Preventing Human Errors

A lot many times it has been noted that the professionals tend to either prescribe a wrong medicine or dispatch a different medication by mistake. Such errors, in general, can be reduced since Big Data can be leveraged to analyze user data and the prescribed medication. It can corroborate the data and flag potential out of place prescription to reduce mistakes and save lives. Such software can be a great tool for physicians who cater to many patients in a day.

Healthcare & Big Data Facts: The Centers for Medicare and Medicaid Services prevented more than $210.7 million in healthcare fraud in one year using predictive analytics.

5. Advancement in Healthcare Sector

Apart from the current scenario, Big Data can be a great benefit for advancement in science and technology. For Healthcare, Artificial Intelligence, such as IBM’s Watson can be used to surf through numerous data within seconds to find solutions for various diseases. Such advancement is already in progress and will continue to grow with the amount of research collected by Big Data. It will not only be able to provide accurate solutions, but also offer customized solutions for unique problems. The availability of predictive analysis will assist patients traveling to a particular geographical location by studying similar patients in that area.

Healthcare & Big Data Facts: Effective use of big data could add $300 million per year to the healthcare industry.

Thus, to sum up, Big Data increases the ability of the healthcare sectors to:

• Predict Epidemics
• Cure Disease
• Improve Quality of Life
• Increase Preventable Care
• Begin Early Preventive Care
• Spot Warning Signs Sooner

Numerous studies and researches prove that technology has tremendously transformed the healthcare sectors. Professor and researcher Ronda Hughes too explains in her research how big data is improving health services.

Improving health outcomes with big data | Source : TEDxUofSC

Although most part of Big Data generated is not fully utilized currently due to limitations of the toolset and funds, it is definitely the future. Invest in the future and leverage Big Data Analytics to be a part of the evolving Healthcare Industry by partnering with Fingent, a top custom software development company with extensive experience in this domain. 

Related Reading: Find out how big companies are using the power of Big Data to enhance customer experience. 

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