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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Digital disruption is what enterprises and technology companies are looking forward to in this age. It’s a welcome change by many organizations – a major shift in something that’s already working bringing with it a multitude of new opportunities and increased growth potential for businesses. Though the term is overused, its impact is real.

Take Uber for instance.

Uber is a digital service that disrupted the taxi industry and changed the way people operate when it comes to commute. The concept was fresh and the impact was huge.

But like every other technology or trend that garners a lot of attention, the idea of digital disruption is also surrounded by myths. These myths impede innovation by giving enterprises false hopes or deterring them completely from ever attempting to achieve disruption. That’s why it’s important to investigate these myths and understand the reality behind them instead of bluntly dismissing them and leaving digital disruption out of a brand’s growth strategy.

Here are a few of the most serious myths surrounding digital disruption.

Disruption is actually a bad scenario

The word disruption itself carries a negative vibe. When people hear the word, they tend to have negative thoughts. But disruption being a bad scenario is still a myth though. Anything that’s disruptive will have both positive and negative effects. It can be a threat to one enterprise and an opportunity to a different one. The bottom line is that disruption is good for a lot of enterprises. The trick is to figure out how to be one of those enterprises for whom disruption will appear as an opportunity.

If it’s a change, it’s disruption

Many organizations have a misconception that any change in an organization brought forth by technology or a change in culture can be termed as disruption. In reality, digital disruption is a significant, fundamental long-term shift in a system and not simply a change. Disruption may be enabled just by the existence of a technology or a trend. It’s a long-term effect which demands enterprises to devise a strategy to thrive in a post-disruption ecosystem.

The benefits of disruption are only for digital giants

This myth exists partly because of the huge publicity that corporate giants obtain for their contributions to technological advancements. There’s a public perception that companies like Google, Amazon etc. are the only disruptors in the game. These companies are often the first to achieve disruption which sets off a chain reaction of secondary effects that impact thousands of SMBs and large enterprises. They simply don’t get publicized much.

Hyped technologies are the most disruptive

This is probably the most widely believed myth surrounding disruption. Many organizations believe that hyped technologies are the most disruptive. For instance, blockchain and AI have been turning a lot of heads for the last couple of years. Companies have started seeing them as highly disruptive technologies.

Contrary to this, in reality, for a technology to be disruptive it has to be a mainstream favorite; widely adopted across the globe and with a number of secondary effects. AI and blockchain aren’t quite there yet.

Conclusion

Without some form of digital disruption, it won’t be easy for organizations to keep up their pace in the coming times. The digital landscape is undergoing dynamic transformations as more technologies keep popping up every year.

To seize the opportunities that disruptive technologies present, you will need powerful digital solutions tailored to complement your business goals. And when it comes to those kind of solutions, AOT is a proven expert. Drop us a message to see how we can help you leverage disruptive tech effectively.

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The role of technology in 21st century is indubitably large enough to influence people’s livelihood and their day-to-day activities. Everything from mobile devices to desktops, tablets, smart refrigerators, and microwaves collectively emphasize how technology in various forms is reshaping the world continuously. This vast expansiveness of technology also generates tremendous amounts of data.

On a daily basis, close to 3 quintillion bytes of data are generated globally. As mobile and other hyped technologies like the Internet of Things gain more momentum, even more data will be generated. Organizations aiming to stay ahead of the curve in a tech-dominated world looks at all these data to unlock the secrets that would help them achieve their full potential. This may sound like a sci-fi/fantasy movie plot, but this is where data stand today in the world – massive sets of random information that hide within them invaluable insights.

Getting the most out of the data an organization generates require the right tools to clean, prepare, merge, and analyze the data efficiently.

That said, here are a few great data analytics tools that organizations can take advantage of this year.

Clicktale

For web analytics today, enterprises rely on Google Analytics, considered to be the best web analytics solution available. Clicktale is basically an emerging rival to Google Analytics. The platform offers behavioral analysis and a multitude of optimization features and tools designed to help enterprises augment their websites.

Oribi

A powerful yet easy-to-use analytics solution, Oribi allows organizations to track their website visitors’ flow. The solution shows how new visitors surf the website and how visitors interact with the various content on the website. Oribi is also capable of tracking specific goals by content type which includes everything from social media to videos and blog posts. It can also assess metrics like downloads, signups, unique views etc.

The main highlight however is Oribi’s ‘smart suggestion’ engine which identifies website visitor flow patterns and recommends ‘events’ based on the identified patterns. The tool requires no manual setup to track micro-conversions unlike its most other rivals.

Kissmetrics

Data aren’t used simply to improve operational performance of an organization and make informed decisions alone. Data drive modern marketing efforts as well. Kissmetrics is the brainchild of marketing expert Neil Patel, offering a feature-rich analytics solution that helps organizations devise better marketing strategies and improve customer engagement. The solution easily integrates with many popular tools and provides a deep marketing funnel-based analytics.

SEMRush

As its name suggests, SEMRush is a very popular online marketing suite offering analytics tools specializing in search. SEMRush includes tools that will aid search engine optimizers in performing audits and developing better keyword and SEO strategies.

In addition, SEMRush also makes it possible for organizations to assess the status and success of their paid search campaigns with respect to the organic keyword performance. One of the most useful features of the suite is that it offers analytics for any site on the web which means competitor analysis is much easier.

Though understanding your company’s data is important to thrive in today’s dynamic market conditions, it’s never easy to find the right tool for the job. When that’s the case, a feasible approach is to build a powerful, bespoke analytics solution from scratch – one that can handle big data the right way. If you are seeking such a solution, AOT can give it to you. Drop us your queries on data analytics to hear back from our experts.

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Developing custom enterprise web applications with select features used to be a pretty heavy investment a decade ago. In addition, getting the software’s user experience right demanded considerable amount of time and money. Not many organizations were willing to make such an investment. But over the years, mostly due to technological advancements, the software industry underwent a revolutionary transformation.

Now any organization can get a bespoke enterprise-grade web application developed with all the right features after choosing the most fitting technologies. Among all those technologies, the most popular would be Microsoft’s ASP.NET – a cross-platform framework resulting from a combination of an MVC structure and a Web API. Its latest iteration, the ASP.NET Core 2.1, features support for real-time web applications and comes with a number of great features that facilitate faster and more secure web development. Above all that, ASP.NET is open source.

Here are a few of those features that reinforce ASP.NET Core 2.1’s value when it comes to web app development today.

HTTPClientFactory

Working with HTTPClient in production software is not an easy task for developers. But with HTTPClientFactory, it will be much easier for them to create and register HTTPClient instances. The instances can be added as a service and operated on via the HTTPClientFactory interface. This is a pretty straightforward feature that hastens the development of larger applications without compromising any important aspect.

The SignalR Library

SignalR is ASP.NET Core 2.1’s open source library that aids developers in adding real-time web functionality to web applications. SignalR comes with APIs for Remote Procedure Calls (RPC) creation, connections grouping, authorization, connection management etc. It also enables bi-directional communication between the client and the server.

HTTPS

The ASP.NET Core 2.1 comes with HTTPS set as default thus streamlining the HTTPS settings in production. The SDK will prompt developers to add installed certificates to the machine’s trusted certificate root. HTTPS will then work seamlessly while debugging is managed locally.

Razor UI Class Library

Like the name suggests, the Razor UI class library is present in ASP.NET Core 2.1 to improve the User Interface in reusable class libraries. By incorporating Razor based UI in a library, the developers will be able to share it across multiple projects essentially making the development easier and hassle-free. For faster app launch, the Core 2.1 looks over the integration of Razor compilation with build processes.

GDPR Compliance

Modern websites should be equipped to handle a large amount of data which makes safeguarding visitors’ privacy a top priority for website/web app owners and developers. ASP.NET Core 2.1 was evidently designed with a focus on privacy requirements. With the framework, it is easier to ensure GDPR compliance enabling visitors to examine, edit, or delete their data from the web application.

Conclusion

Over the years, the software development industry was subject to a number of evolutions owing to the advent of new technologies and frameworks or refinements of the existing ones. But despite the increasing competition and changing development ecosystems, ASP.NET managed to retain its dominance in the sector. ASP.NET Core 2.1 again emphasizes that the popular Microsoft framework won’t be surpassed any time soon.

Thinking of utilizing a powerful ASP.NET application for your organization? Get in touch with the ASP.NET experts at AOT to understand everything about custom ASP.NET applications.

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