To thrive in today’s marketplace, organizations need to wield the right tools and technologies. Technology can certainly make all the difference for a growing business, enabling it to establish a strong digital presence all the while enhancing its capability to handle a number of business challenges and large volumes of data to begin with.

For modern businesses, websites aren’t just their online identities. A website is essentially a web portal that offers a wide range of information pertaining to the business from a number of credible, authoritative sources in addition to having pages that detail the services/products offered by the business. Web portal development isn’t simple however. For the web portal to serve its purpose and catapult a business to new heights, it should be built by experts who are aware of the latest tech and development trends.

That said, here are a few such trends that would drive innovation in web projects.

AI and Machine Learning

The website of a business will potentially generate data that hide critical insights. A modern advanced web portal will have a neural network backing it that trains itself on the tremendous amounts of data generated thereby becoming capable of performing complex analyses and make predictions that could help with decision-making. Companies are willing to invest in machine learning algorithms to do this and more.

Such algorithms can be instrumental in processing large datasets and estimating conversions. For content-sharing web portals, such algorithms can even recommend efficient and smart ad-placing for the best results.

As we speak, intelligent AI-based solutions are already making a difference for businesses worldwide – understanding performance history, analyzing uncovered insights, compiling forecasts, designing marketing/promotional campaigns, and even tailoring the best possible user experience.

Computer Vision

Though Computer Vision is still considered a scientific discipline rather than a usable technology, its potential spells major changes across various sectors including web development. Web apps can be imbued with the capability to extract critical data from images, videos, or real-world environments. This can be particularly beneficial to large businesses in the retail sector. Computer Vision can be combined with other trends like Augmented Reality, and can further enhance the potential of modern-day biometrics.

Imagine a web portal that allows authorized visitors to upload images that are then analyzed to tailor the visitors’ experience on the website later in more ways than one.

Cloud Service Management

With more enterprises shifting to the cloud, the growth of the cloud services industry has been exponential. Enterprises can choose from a wide array of services that enhance everything from operations and problem-solving to security and performance analytics. The challenge here is to monitor the usage of various cloud services and assess how they are billed.

A web portal gets augmented capabilities like withstanding massive traffic spikes and guaranteeing maximum performance thanks to the cloud. But this approach requires a reliable cloud services management methodology that helps control the spend on cloud services and tailor the size and scalability of the enterprise’s cloud strategies.

Blockchain

Sophisticated enterprise-grade platforms aren’t devoid of vulnerabilities especially when it comes to security. This is where blockchain is going to make a difference. With blockchain technology, enterprise systems support multi-tier interactions, and are granted unparalleled security and transparency. Blockchain can be particularly effective in fully integrated web portals that privately store something of great value or trade cryptocurrencies across various user accounts.

In addition, websites or portals integrated with blockchain technology can theoretically read visitors’ blockchain to show the most relevant information on the website for quick conversion. Blockchain also presents opportunities for web designers to design interactive experiences that will dynamically change based on visitor preferences.

AWS and Microsoft Azure offer blockchain as a service which is a testament to the fact that it’s a technology worth investing in and deserves to be treated as a valuable component that can secure large companies in the future.

AR and VR

This list wouldn’t be complete without Augmented and Virtual Reality – two of the hottest technologies today. AR and VR experience is what many businesses are aiming for in their websites and mobile apps. The technologies allow businesses to leverage immersive 3D content and engage users with unique experiences that they won’t be forgetting anytime soon.

Endnote

There are many more trends worth mentioning but we thought we should go with the ones that generated huge hype in a short time instead of simply taking benefits and service potential into account. AOT Technologies is an accomplished website and web portal development company with ample expertise in leveraging new-gen technologies like AI, AR/VR, IoT and Blockchain. Get in touch with us and let us show you how your website should look like to thrive in a super competitive, tech-dominated future.

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In order to ascend in today’s world where technologies are capable of making and breaking businesses, organizations are required to migrate their enterprise applications to the cloud. This amplifies the usefulness of enterprise applications manyfold. For example, an enterprise app that supports 100 internal users may support 100x more users on the cloud. Such features are a standard nowadays for enterprise-grade apps that are accessible to a wider value chain-facing user base.

Because traditional enterprise applications and their data are open to a larger audience now, they are expected to deliver the best user experience which is where technologies like AI and Machine Learning come in. Modern enterprise applications are expected to deliver smart, contextual experiences to customers and stakeholders. The cloud serves as the best platform for cutting-edge technologies like AI to augment a traditional enterprise application without hassle.

As a matter of fact, once on the cloud, the apps get even more benefits in the form of an improved cost structure, great scalability and flexibility, and the ability to quickly adapt to changing business needs. But all of these achievements that organizations expect can only be obtained after successful migration to the cloud. It’s seen by many organizations as a particularly complicated procedure.

But cloud migration doesn’t have to be that complicated and difficult. With the right kind of planning and good execution, cloud migration can be successful.

That said, here are the steps every enterprise should take before proceeding with executing their cloud migration strategy.

Application Inventory Assessment

Before migration begins, it’s a good approach to have an application portfolio inventory. The inventory will have the enterprise’s applications categorized. It’s important to assess this inventory and the applications’ dependencies including their physical and virtual server configurations, network topology, compliance requirements, security mechanisms, data dependencies etc.

Such an assessment would enable enterprises to determine an approach to get the best results from the migration. For instance, the ‘Modern Apps’ category in the portfolio inventory might already be on the cloud platform or can be easily migrated there. The ‘Legacy Apps’ category in the portfolio could present a big challenge when it comes to cloud migration. The risks may be too big. Then there are other enterprise-grade applications like web applications and Java applications. The enterprise would know which category they should begin with for the best results.

Complementing this approach, modern IT services also grant enterprises with the option of choosing the degree of cloud services for each of their applications while assessing the benefits of migration and estimating the cost of it. This doesn’t apply to legacy apps however. But cloud service providers can still provision servers and storage for such applications to run like they used to, without compromising the reliability users expect from them.

The most valuable opportunity, on the other hand, is associated with the migration of the ‘other’ kind of apps in the enterprise – the third category which includes enterprise-grade Java apps, web applications, and the likes. Migrating such apps to the right kind of public or private cloud results in a lot of cost savings.

Creating a Plan

Migrating and modernizing that third category of apps mentioned above requires careful planning so as not to add complexity, challenges or costs. The plan should take into account a number of factors including but not limited to:

  • The architecture of the application to be migrated and its dependency on its infrastructure.
  • The application’s security policies and tools involved that enforce these policies.
  • The tools that manage the accessibility to the systems on which the application runs.
  • Tools used by the team to deploy, manage, and troubleshoot the application
  • Application’s unique performance characteristics
  • Application’s awareness when it comes to the underlying network & hardware topology

Provided that the cloud service provider is experienced, the aforementioned factors can help your enterprise execute a migration strategy that appropriately prioritizes app migrations.

Applications that are already on the cloud with no dependencies apart from the immediate application stack can be managed with a managed public cloud service. Other enterprise apps that have multiple dependencies and relationships in the data center ecosystem should be quickly migrated to a managed private cloud.

Quick Migration for Cost Savings

Many enterprises prefer migrating with the help of their in-house team and choose a conservative approach to migration to cut costs. However, this approach too often ends up increasing costs in the long run; one major reason for this being the fact that the enterprise is essentially running two infrastructures during the migration incurring costs on both.

The best approach to mitigate risks while realizing cost savings is a quick migration. It’s possible to do this without assistance provided the enterprise invests a lot in rigorous planning. However, a more feasible and risk-free way is to enlist a cloud partner with expertise in public, private, and hybrid cloud.

The right cloud service expert can, within the budget, recommend the necessary services needed for successful migration based on the application portfolio inventory and the enterprise’s specific preferences. With their help, enterprises can get applications shifted to the cloud quickly and economically without being concerned about risks.

Conclusion

Moving applications to a managed public and private cloud properly ensures significant operational cost savings (of up to 60%) owing to the cloud’s optimized hardware utilization and the availability of efficient administration tools. But the pivotal component that influences the success of a cloud migration procedure is the expertise and experience of the party performing the migration.

If you are looking for a partner with the required expertise to make the migration happen without issues, you are at the right place. AOT Technologies, over the years, have been building our reputation as a reliable IT service provider specializing in software solutions and cloud computing technologies.

We have a team of qualified cloud experts who know their way around the most widely used cloud services and widely adopted cloud migration strategies. AOT is also fully capable of devising a migration strategy to deliver the outcome and benefits you desire cost effectively. Get in touch with us today.

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Artificial Intelligence is now seen as a critical component for enterprise digital transformation. AI can take many forms to help businesses achieve accelerated growth and improved operational performance in highly competitive markets. Among the various forms of AI, voice interfaces are probably the most demanded. For businesses, an AI-driven voice interface is known by a different name – Conversational AI.

The benefits of conversational AI seem to be expanding without limit as AI continuously evolves. From improving customer service to increasing online sales revenue, the wide array of benefits granted by conversational AI are what businesses are willing to invest in.

As a matter of fact, Gartner predicts that by 2020, 25% of customer support & service operations will be driven by virtual assistants across various engagement channels.  

So the question now isn’t about how a company should implement conversational AI. It’s more about where they should start. That said, this blog covers a few major aspects that make a great conversational AI app. Make sure your journey to implement and leverage conversational AI is along the right course.

Implementation efforts centered on the business case

Before you start implementing conversational AI for your business, make sure that you can articulate the business case as well as the returns you expect from the technology. If you aren’t sure about the latter, work collaboratively with your AI services partner to help define the value you would like from your conversational AI.

With your efforts centered on the business case and the expected value, it’d be easier for you to deploy the right technology by making the right design decisions. The key is to stay true to the defined goals. As long as you are sure of the desired result, you can shape the implementation properly while taking into account the business constraints such as time or budget. This way your tech will only possess features that your business really needs.

A UX that streamlines customer journey

The AI-based solution’s adoption and revisit rates depend on a number of factors out of which the UX is possibly the most important. Even if the conversational AI solution features attractive dialogs and integrated data that facilitates personalized responses, it would still appear underwhelming if it lacks a solid user experience.

For a conversational AI, the UX needs to take a few major factors into account. The solution should speak and converse like a human. This doesn’t mean it should pretend to be one. Users may expect digital customer support employees to participate in small talk, remember, understand context, and be smart.

Many companies try to use chatbots that pretend to be humans when interacting with potential customers. This is likely to backfire as the approach can break the trust the end users have on the solution. The conversational app should be able to resolve the user’s issue. If it fails to do so, the user will approach a different channel with a better alternative that can serve them better.

Information pertaining to things that are out of scope for your intelligent bot should be provided early on in your customers’ journey; at least as links. The personality of the bot is also important. It can be humorous, sassy, or formal with a rich UI coupled with modern design standards.

The key is to have the conversational app cover the user journey from the beginning to the end while drawing out a satisfactory conclusion for users with their issues resolved.

A scalable platform that can handle multiple intents

When going for an AI-driven conversational bot, it’s best to start small. Implement the idea as a small project and develop it further in phases after assessing the initial results. Choosing a scalable platform here is a great approach that helps you capitalize on your initial investment and gives you a lot more options when moving forward.

The user will want to achieve something with the app, right? There will be an ‘intent’. You should ask yourself how many intents your chosen platform can handle. Various conversational AI platforms have different capacities when it comes to handling intents. The platforms will have different algorithms to process the intents. Though Machine Learning capabilities make it easier for conversational AI applications to learn intents, such features still won’t be enough if there are hundreds of intents over multiple business departments, divisions, languages, and geographic regions.

There are platforms that are powerful enough to deal with a large number of intents but there tends to be a limit at present which forces enterprises to develop multiple solutions to get by. The bottom-line here is that the conversational AI platform should be capable of delivering precise responses depending on user intent and context. It’s not easy but it is practical provided the chosen platform is highly scalable.

Top-notch security and encryption standards for customer data

Conversational data can be a goldmine in disguise for businesses. Such data can be analyzed and understood much easier than the data gathered from calls. However it also presents a great risk to organizations. They will need to secure the data and ensure the privacy of their users. Any compromise in the conversational data could end up causing your customers to lose trust in your business instantly.

The AI solution should be capable of anonymizing the data while also making it easier to understand the intents for analytics. The identifiable data can be replaced with placeholders. This way the customer identity will remain anonymous while the intent will be clear to your organization for analytics purposes. If there are transactions involved, the application should have robust encryption mechanisms to encrypt the data that would be transmitted over the internet.

Your organization should be certain about the information you wish to collect from customers, the security practices that can be implemented to safeguard the data, and practices to make good use of the data without compromising the privacy of customers even before building a conversational AI application.

The value of the AI solution depends on its capability to continuously learn and improve. Building one such solution requires great proficiency in AI and associated technologies and years of experience in building enterprise-grade business solutions. AOT has both, and we can help you utilize a powerful conversational AI program as well. Talk to our experts today to learn more.

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With a new year around the corner, mobile app developers around the world would be gearing up to meet and overcome new challenges, and augment their skills. Generally, app developers will be keeping an eye on new technologies to figure out techniques that could help them develop applications better and faster.

Amidst all the excitement, while researching new technologies that influence app development, developers tend to forget about the one major aspect that helps an app succeed in its humble beginning in an app store – intuitive UI.

A mobile app doesn’t stand a great chance to be successful in a highly competitive marketplace. It needs to be unique when it comes to serving its purpose, and users should simply have a great time using the app. After all, first impression is what helps an app gain traction in the store. Thousands of apps in the Google Play Store disappear into oblivion in on a daily basis; a major reason for this being the lack of a good UI.

That said, here are a few UI design trends that developers should keep in mind in 2019.

Illustrations for user engagement

Content is still the king when it comes to user engagement. And content can take many forms. New trends suggest the use of illustrations instead of bland text content to convey messages to app users and keep them engaged. The idea is to tell stories using images and videos. Meaningful illustrations that provide information of value to users can impress them more than a plain text guide. Illustrations, used wisely, can transform a regular app into a vibrant one resulting in a great first impression.

Overlapping effect and gradients

Overlaps create a structured user interface adorned with colors, text or image. Due to the fact that displays have better color production today, there was a significant increase in the use of gradients in mobile app UIs. Elements with gradients make things look more natural. We will certainly see more app developers utilize overlapping effects with bold colors and gradients in 2019.

Virtual Reality

Virtual Reality (VR) made it to this list because it shows great promise. We saw AR making itself known this year as one of the hottest app development trends. We will be seeing VR do the same in 2019 as more VR devices keep getting introduced to the market and made available at reasonable price tags. VR enhances user interfaces in a way that would intrigue people to check out the app once and keep on using the app for the unique experience.

Typography

It’s not just the colors and images that should be given attention in a user interface. The font matters as well. An appealing font for a heading or description can tempt users to go through the text. Typography can complement a good narrative adding to the user experience. While the text style catches the attention of app users, narrative illustrations engage them. This way they won’t miss important info that a brand wants them to see. Typography and unique text styles would play a key role in app user interfaces in 2019.

Frameless screens

This year, there was a rather strange app design trend that turned many heads – frameless screens. Many designers went with an app design that doesn’t have frames, and the responses from users were positive. Despite the good start, not all designers were willing to take the risk of using frameless screens in apps this year.

But now that mobile phone manufacturers have started coming forward with frameless smartphones, more app designers can be expected to adapt to new trends and try out ‘frameless’ screens in 2019. Many modern devices also have curved edges that naturally impose design restrictions including sharp edge elements. Frameless screens can shine here creating a fresh look and a unique experience for mobile users. Its applications in both mobile app design and web app design makes this trend one of the best design trends in 2019.

Voice-assisted UI

Advancements in AI and Machine Learning have helped chatbots and communication assistants become the most popular trends in 2018. Many websites and mobile applications have also started using voice communication to enhance user experience. As bots and voice interfaces become common, app developers will be thinking more about leveraging voice-assisted user interfaces to serve multiple different purposes in an app, delivering a more interactive experience to users.

Conclusion

For the app development industry, 2019 will be about innovative combinations of a number of great app design and development trends. There will be a renewed emphasis on designers’ knowledge on new trends and techniques. As always AOT keeps ourselves updated on all new app design & development trends so our clients can get the best of new technologies.

Let us know your queries. Talk to our experts today.

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Over the years, businesses utilized a number of advancements – both technological and industrial, to accelerate their growth and increase their profits. Of all that which businesses have leveraged so far, one particular advancement stands out for its massive potential – Data Analytics.

With extensive data analytics, businesses can uncover valuable insights from the tremendous amounts of seemingly senseless and random data they generate. Armed with this information, organizations can tweak their business strategies for better results.

What makes this ‘big data’ awesome is the fact that it shows great promise for all types of enterprises irrespective of their sizes. Through big data analytics, enterprises can not only increase the revenue generated but also identify security vulnerabilities and gaps in their services and products. Big data is still an evolving technology however, and like every evolving technology, it is also shrouded by a lot of myths and misconceptions.

This blog debunks a few of the most popular myths that deter businesses from checking out big data.

Myth 1: All that matters is size

The first thing that anyone can think of when hearing the term ‘big data’ is the size. As such, there seems to be a myth that the main defining trait of big data is the sheer size or volume of data involved. This is not the case. Though size is certainly one of the main characteristics of big data, it isn’t the only important one.

The volume of data involved demands sufficient storage systems. But big data also requires high velocity data processing mechanisms to deliver relevant, more up-to-date outcomes. The data come from various sources which means the outcome may vary from what was expected. The data being handled by big data should be also be veracious and the insights from these data should provide value.

From all these facts, we can infer the most important traits of big data other than size or volume.

Velocity. Variety. Veracity. Value.

Neglecting these features can result in an improper implementation of big data that can complicate simple solutions and deliver irrelevant results while wasting resources.

Myth 2: Big data is a collection of high quality data waiting to be processed

Big data is a collection of a lot of data sets that can include both relevant and irrelevant data. All that data don’t necessarily have to be of high quality. As a matter of fact, without proper data filtration mechanisms, big data analysis can result in a lot of data quality errors.

Many organizations opt not to clean the data before processing to avoid the hassle of dealing with such large amounts of data. Data cleaning also requires the organization to invest more in big data. This practice most likely ends up with big data failing to do what it’s expected to do. For big data analysis to be effective, the data should be cleaned. This helps the system provide more accurate results.

Myth 3: Big data predictions about a business’ future are highly accurate

This myth is based on the assumption that the volume of big data is directly proportional to the accuracy of big data analysis results. The more data one feeds into the system, the more accurate the results will be. But that’s a myth however. Data certainly hold great value for modern businesses but there are other factors that are just as important if not more.

A big data system will never be able to accurately predict a business’ future by simply analyzing data. Factors like economy, technological advancements, human resources etc. directly influence the success of a business, and data simply won’t be factoring in everything that directly or indirectly influence the business’ success. What big data can do is extrapolate future possibilities by comparing and analyzing historical data.

If the business uses real-time data instead, the system will be delivering predictions based on a probability theory i.e. the results still won’t be certain. However, it’s true that the accuracy of forecasted results will be higher if the data fed are relevant and of good quality.

Myth 4: Big data is expensive

That’s the myth all right. This is the fact – big data ‘was’ expensive. Back when big data started turning heads for its potential, only big organizations and government bodies stepped forward to invest in it. The investments weren’t small either as organizations required large-scale data centers and talented big data professionals to wield big data properly.

But time has changed. As big data garnered praise from all directions, many vendors stepped forward reducing the licensing costs of big data tools and making them much more affordable to small medium-sized businesses. In addition, new tools and techniques are also being introduced to help smaller businesses perform big data analyses.

Myth 5: Big data is centered on machine learning technology

Machine learning certainly is associated with big data. But big data isn’t centered on machine learning. New generation big data analyses make use of complex machine learning algorithms to derive sensible and relevant insights from massive data sets. That’s the whole concept of Machine Learning – using data to uncover information that can help an organization or an individual make meaningful decisions. Both technologies are used in conjunction to deliver expected results. Big data can exist without machine learning.

Myth 6: Big data is all about analytics

What’s strange about big data is that it has multiple definitions, and most of them are accurate. A simple Google search would get you at least a dozen different yet valid definitions of big data from various sources. While some consider it as massive data sets, others see it as an analysis technology that can process massive data sets. The fact is that big data is something much bigger than data analysis with many capabilities to solve a variety of problems with data.

Conclusion

For big data to truly live up to its name in an enterprise, it should be seen as something more than a lot of data being processed. It needs to be managed and overseen by experts who can tell myths from facts.

If your enterprise is planning to leverage big data and is looking for expert guidance or automated solutions, you are at the right place. AOT’s deep expertise in a wide array of technologies including big data and AI/ML can ensure maximum big data ROI. Drop us a message to get started.

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