By Thierry Bonfante, Chief Product Officer, Unqork

The race to the AI-powered enterprise is on, but most organizations are still trying to figure out where to start. Now, the Unqork Enterprise App Cloud provides a powerful, scalable, and future-proof way forward.

Besides accelerating development of AI-enabled apps, Unqork addresses critical underlying challenges like security and compliance, so businesses can innovate without taking on the burden of maintenance and tech debt.

I. Introduction

Ready or not, AI-enabled applications are coming, and their impact is going to be enormous. Goldman Sachs analysts predict that AI tools alone could add $7 trillion in net-new economic value annually. With so much to gain, the vast majority of C-suite leaders—85%, according to Accenture—want to increase their AI investments.  

Under competing pressures to both innovate and reduce costs, business and tech leaders cannot afford a wait-and-see approach, especially since the gap in performance between digital leaders and laggards is already huge. The CAGR of digital leaders averages 6X that of laggards, according to McKinsey, and AI is only widening that gap. “Over the past three years, the spread in digital and AI maturity between leaders and laggards has increased by 60%,” McKinsey analysts wrote in early 2024. 

Yet, so far, only 9% of companies have adopted AI technology in a significant way, MIT researchers have found. Because the technology is both so powerful and so new, the list of concerns of business and tech leaders is long and keeps growing. AI technologies, along with their potential use cases and regulatory requirements, are evolving so quickly that leaders are understandably hesitant to make major investments, despite the potential of outsized returns.

Over the past three years, the spread in digital and AI maturity between leaders and laggards has increased by 60%.

McKinsey Digital, 2024

II. The challenges to adopting AI-enabled applications

First of all, let’s address one misconception that can still stall discussions about implementing AI. Not that long ago, AI initiatives required large teams of vanishingly scarce data analysts and data scientists. They had to build bespoke AI models and do the hard and complex work of managing enormous datasets, data warehouses, underlying hardware, etc. And they still needed highly skilled developers to write code in order to integrate the AI models into enterprise applications–code that then had to be continuously managed, upgraded, and secured.

This is no longer the case. Now, businesses can leverage prebuilt AI models designed to solve for very specific use cases. They can even work with trusted partners like Google’s Vertex AI or Amazon’s Bedrock, which allow customers to deploy and easily manage a variety of AI models through a managed service on their own infrastructure. However, leaders still face a number of challenges when it comes to integrating those AI models within applications, including:  

• “Where do I even start?”: While leaders have little doubt about AI’s importance, they’re still trying to separate the hype from reality. They are unsure how they can tackle AI in a practical way and actually move the needle for their organization. Meanwhile, both the number of AI technologies and related regulations are evolving so fast that many leaders are hesitant about implementing AI. They want to avoid unnecessarily high risk ranging from compliance issues and poor ROI to project failure due to unforeseen complexities. 
• Talent gaps and stifling tech debt: Nearly 70% of IT leaders report that tech debt is holding back innovation. Because organizations are spending so much just to “keep the lights on,” it’s no surprise that there is a talent gap, especially an AI talent gap. These talent and tech debt bottlenecks leave little room to tackle AI and innovate.
• Security risks. While AI outputs may be distinct from other kinds of enterprise data, they can still contain sensitive information—especially when businesses train AI tools on their proprietary data. Not surprisingly, CSO recently reported that 71% of organizations were concerned about data privacy and security when it comes to AI. 
• Compliance and data lineage risks: While regulations around AI are still in flux, there is little no doubt that they will grow more, not less, stringent. And AI has raised all kinds of concerns, including “privacy, cybersecurity, regulatory compliance, third-party relationships, legal obligations and intellectual property,” PWC analysts warn. Whether firms choose proprietary LLM , third-party solutions, or a hybrid model, data lineage and “traceability”—the ability to track AI outputs, how they are used by internal systems, and who sees their output—is a critical concern.

III. How Unqork’s unique approach helps enterprises leap-frog AI challenges

With deep and wide experience in some of the world’s most highly regulated industries, the Unqork Enterprise App Cloud lets you create, secure, and manage enterprise applications in the cloud and unleash the power of AI. Unqork is uniquely able to solve the core challenges that are holding enterprises back from leveraging the game-changing power of AI within their applications.

1. Flexible, open, and future-proof innovation

Historically, low-code/no-code and other SaaS providers have created “moats” that lock in customer IP and data. Unqork’s approach is completely different. With an open architecture built on standardized web technologies, you never have to rip-and-replace your existing ecosystem. You can easily integrate with third-party solutions, legacy tools, AI solutions, and virtually any emerging technology–all with zero code. 

In fact, Unqork has gone one step further by becoming the first full-stack enterprise development platform to make its platform spec available as open source. That means customers and partners can create innovative components designed to interact with Unqork’s platform. 

Finally, Unqork’s unique architecture means we can handle all application upgrades and maintenance on an ongoing basis, because your apps are pure configurations. We take care of the underlying code and infrastructure. In other words, you finally get to focus on innovation and gain a truly scalable, future-proof path to the AI-powered enterprise. 

2. Rapid, intuitive development of AI-enabled applications that’s 3X faster 

The Unqork Enterprise App Cloud enables you to build complex, mission-critical apps 3X faster, all with a 100% drag-and-drop visual designer. Unqork also provides business accelerators targeted at specific use cases. And Unqork makes it easy to connect to third-party applications, databases, on-premise systems, and cloud data into Unqork–and quickly can scale those integrations across the company. 

In addition to these capabilities, Unqork’s GenAI Connector streamlines the process of integrating and configuring a connection to a third-party GenAI tool within an application. With the GenAI connector, organizations can: 

• Establish connections to the GenAI tool of their choice, choosing the vendor that best suits their policies and use cases. 
• Customize the template for their specific use case, and test to ensure the integration is working as expected. 

By accelerating development and taking on the burden of managing applications across their lifecycle, Unqork minimizes risk and democratizes the adoption of AI, while providing a scalable path to unleashing it across the organization.

3. Robust, enterprise-grade security you don’t have to worry about

Ideally, all of an organization’s data resides within a single-tenant environment, and it never leaves its own ecosystem. However, AI depends on data for its power, including proprietary data for many use cases. 

To secure both proprietary data and the output of AI that draws on that data, businesses can partner with vendors that keep both data and AI solutions in a single-tenancy cloud environment. Or they can go one step further and leverage an open sourced LLM that enables firms to copy the model and run it entirely on their own proprietary systems. 

However, businesses still need to secure outputs of any AI integration as they move to other systems and are served up to customers. The Unqork Enterprise App Cloud provides a powerful way to securely leverage AI across the entire software development lifecycle (SDLC), all from one central location. As a result, enterprises can: 

• Own their own data and encryption. 
• Rely on a single tenant architecture with certifications for FedRamp, SOC 2 Type II, ISO, HIPAA, and more. 
• Quickly and efficiently apply role-based access controls (RBAC) at both the module and component level. 

4. Compliance and data lineage of application outputs

Imagine that a regulator asks you to show the exact output from an AI integration at a specific point in time or that you need to review an interaction a customer had with your AI chatbot. Without native data lineage capabilities in place, organizations could face a long and costly process involving third-party consultants. 

The Unqork Enterprise App Cloud enables peace of mind with native support for data lineage of AI outputs. With Unqork, you can go back to any point in time and see what data outputs were generated or modified by the integrated AI tool and what user or customer interacted with the data in that moment.  

IV. So where should enterprises start leveraging AI within their organizations? 

In 2023, less than 5% of enterprises used GenAI-enabled applications in production environments. That number is expected to skyrocket to more than 80% by 2026, according to Gartner. And Unqork is in a unique position to help enterprises unleash AI in the context of very tangible, impactful use cases across their organizations.

Instead of endless debate about AI’s possibilities, Unqork customers can quickly deploy AI solutions with a clear, measurable, and easily achievable objective, rather than tackling AI for its own sake. And for the vast majority of businesses, it’s not the most powerful or creative AI use case that will win the race, but solutions that are straightforward and user-friendly. Examples include: 

• Personalize customer journeys. From natural online conversations and enhanced sentiment tracking to pixel perfect-experiences, you can leverage AI to delight customers with highly personalized, differentiated journeys. 
• Boost employee productivity. You can use AI to contextualize data and analyze abstract information to make smarter decisions more quickly. 
• Accelerate the digitization of complex workflows. Tap into all your data to orchestrate complex workflows and digitize manual processes—without writing a single line of code.

Instead of endless debate about AI’s possibilities, Unqork customers can quickly deploy AI solutions with a clear, measurable, and easily achievable objective.

McKinsey Digital, 2024

Here are some of the ways that Unqork clients are powering their use cases with AI: 

Google’s Gemini + Unqork: AI-powered client-facing advisor interactions

It has traditionally taken financial advisors significant time and effort to prepare for client meetings. They need to gather details about clients, their accounts, and performance of those accounts from across multiple CRM systems and market feeds.

By leveraging Gemini together with Unqork, wealth management firms can automatically provide advisors with intelligent client and portfolio summaries, meeting background, and cross-sell opportunities. As a result, a process that requires hours of the financial advisor’s time and effort is complete in a matter of minutes. 

Intelligent Document Processing (IDP) + Unqork: Intelligent data extraction and document processing

Many enterprises still rely heavily on manual document capture and data extraction to drive their most sensitive processes. You can change the game by combining IDPs with AI-powered intelligent data extraction and document processing with the Unqork Enterprise App Cloud. Together, they enable highly regulated organizations torapidly build and effectively power complex data workflows and seamless experiences for their customers and employees. Use cases include: 

• Loan operations. Rapidly automate the extraction of key data points from complex credit agreements, post-process to meet formatting requirements, stage for review, enrich with key reference data, feed into the golden source, and release to downstream systems.
• Investment guideline compliance. Automatically cull guidance requirements for specific clients from signed documents, and implement restrictions to account activity. 
• End-to-end underwriting. Empower underwriters to focus on their highest-value activities, and win more business by rapidly and accurately ingesting submissions data, automating triaging, and accelerating submission response times.

V. Unqork: A faster, more future-proof path to AI-enabled enterprise applications

From accelerating time to value to providing a sustainable approach to security and compliance, Unqork is uniquely positioned to support the AI-enabled enterprise in a time of rapid technological and regulatory change. 

To learn more about what your organization can achieve, reach out here.

Unqork’s Quarterly Platform Release gives enterprise organizations access to a range of powerful new capabilities for building smarter, more impactful applications, including an accelerated path to integrate third-party or proprietary AI tools and rapidly deploy AI-enabled applications. 

With these advancements, Unqork is empowering enterprises across the financial services, insurance, and public sectors to create smarter, more dynamic applications than ever before.

What’s in this release

• GenAI Connector: Build AI-enabled applications with ease by seamlessly integrating third-party or proprietary AI tools, enabling rapid application deployment. 
• Application Versioning: Streamline collaboration and simplify application maintenance by creating and managing multiple versions of the same application simultaneously, minimizing disruption and boosting productivity.
• Data-Centric Development: Ensure peak application performance and data integrity by seamlessly integrating data models within your module using a simple drag-and-drop interface with Data Models & Schemas. Additionally, simplify API endpoint configurations and easily return data in the desired format without complex workflows with the new Visual Query Builder.
• Vega Tables: Take back control of your data with Vega Tables, a centralized table component that unifies your data into a single, easy-to-manage location.
• Operations Builder: Simplify complex UI interactions with minimal manual configuration. Build complex logic against a given set of events and operations, enabling the creation of dynamic and responsive user interfaces.

GenAI Connector

Unqork’s GenAI Connector simplifies and accelerates the creation of secure, enterprise-ready AI-enabled applications–and eliminates the need for code and the tech debt that comes with it.  With GenAI Connector, Unqork takes on the burden of maintaining applications throughout the entire lifecycle—empowering you to focus on innovation.

Benefits:

• Simplify the integration of GenAI solutions into your applications through an intuitive connector that accelerates modernization efforts.   
• Rapidly and iteratively create AI-enabled applications with Unqork’s 100% drag-and-drop visual designer.
• Create AI-enabled applications equipped with enterprise-grade security and compliance.
  

See GenAI Connector in action

Published Application Versioning

To release business-critical features given today’s complexity of large, interconnected applications, enterprises must implement robust processes like CI/CD, comprehensive testing, and manual QA to coordinate parallel work across teams and minimize errors. Published Application Versioning helps solve this challenge by allowing enterprises to run more than one version of an application at a time and eliminating the need to update every connection in an application with each new version. Now, you can create and test multiple versions of the same application in parallel, without any disruptions.

Benefits

• Easily promote and test without disrupting development, increasing speed to market.
• Enable multiple teams to collaborate simultaneously on the same application, boosting productivity and innovation.
• Leverage enhanced application security measures, including disclosed application patch numbers and semantic versioning
  

See Published Application Versioning in action

Data-Centric Development

With new Data-Centric Development features in the latest release, Creators no longer have to structure and validate data manually or rely on workarounds that can compromise application quality. With Data Models & Schemas, users can seamlessly integrate data structures throughout workflows, speeding time to market, increasing application quality, enhancing security, and lowering technical debt. Then, Visual Query Builder allows users to easily access their data by quickly configuring API endpoints and returning data in the desired format without complex workflows.

Benefits:

• Rapidly build schema-compliant user interfaces, and simplify data extraction to achieve faster time to value.
• Seamlessly integrate data structures for enhanced data quality and application performance.
• Lower tech debt by improving development efficiency, enhancing data governance, and reducing errors.
  

See Data-Centric Development in action

Vega Tables

Vega Tables eliminates the need to sort, search, and manipulate data across multiple tables by consolidating all functionalities into a single Table component. In addition to providing a cohesive and comprehensive solution for data management needs, Vega Tables offers responsive, native-feeling interfaces similar to spreadsheet environments.

Benefits:

• Save time and energy by quickly gathering and organizing data into a singular tabular display, and seamlessly navigate and edit data.
• Effortlessly edit and input data by providing users with a seamless, familiar spreadsheet-like experience for data entry and management.
• Build insight-driven applications by enabling advanced filtering, sorting, and search query capabilities.
  

See Vega Tables in action

Operations Builder

Instead of manually hard-coding values, Operations Builder provides Creators with a modern UI allowing them to easily build and customize operations and events for Vega Tables, including filtering, adding rows, removing rows, navigating to different table pages, and more–all with zero code. As a result, users no longer have to run operations manually in the Table component and can instead use scalable logic components to control and trigger them.

Benefits:

• Simplify the configuration process by providing a guided, easy-to-read experience for Creators, expediting time to value. 
• Deliver a seamless and intuitive interface that eliminates the need for manual entry to create tailored Table logic.
• Provide end-user flexibility and customization by unlocking the ability to review, organize, and search data in their Tables more efficiently and tailored to the business needs.

See Operations Builder in action

 

By Bassam Chapatini, CTO at Unqork

I. Introduction

When ordering milk on a grocery delivery site, you can select exactly the item you want in just a few seconds via a series of drop-down menus—the brand, the source (almond, oat, cow), the quantity, the number of items, the fat content, etc. In other words, you use structured data. 

Now imagine putting all that information in an email, i.e. using unstructured data. It would obviously take longer to write the email, and longer for the shopper to search for your email and decipher exactly what you want. 

But you don’t just waste time. You also exponentially increase the chances of your order going wrong. Maybe you forget the name brand you prefer, or accidentally misspell it. Maybe the store doesn’t even carry that brand. Maybe the shopper misses the fact that you wanted oat milk instead of cow’s milk.  

Given all the ways unstructured data can go awry, why would you ever write an email when you could use a dropdown menu instead? And yet, enterprises are still developing software with unstructured, language-based code (and that includes low-code and no-code platforms, as we explain below)—the equivalent of the slow, error-prone email approach to ordering groceries. 

However, there is a new development paradigm that shares the speed and precision of the structured, drop-down menu approach. In this white paper, we explain why an unstructured, code-based approach to development is no longer necessary and how the Unqork Enterprise App Cloud: 

• Transforms all software components into 100% structured data—no code required, ever. 
• Dramatically speeds and simplifies the entire SDLC. 
• Helps creators focus on innovation and value creation, because the Enterprise App Cloud handles security, compliance, upgradeability, and more—all on an ongoing basis.

II. What is 100% data-defined development? 

The best way to understand the Enterprise App Cloud is to compare it with a technology that is already familiar—cloud computing. Essentially, it is to application development what the cloud is to hardware. They both provide a strategic layer of abstraction that enables much faster innovation, more flexible resource usage, and economies of scale. 

Think about computing before the cloud. Enterprises were in the business of buying, implementing, and managing computing hardware. True, over the years all kinds of incremental innovations made the job incrementally easier, from layouts that optimized cooling to the virtualization of servers to increase utilization. But managing servers was still hard work requiring a high level of skills. And every enterprise was doing it.

Cloud changed all that. Cloud computing took advantage of all those incremental innovations in server management, but it went one step further by completely abstracting the hardware layer, and thus making a hardware problem becomes something easily manageable through software. That means enterprises can get rid of their servers altogether—and the time, expense, and complexity of running a homegrown data center. 

If you ask a technology leader today what kinds of servers their organization’s applications are running on, chances are they have no idea. And even if they do know, the cloud provider could spin up an entirely different set of servers tomorrow. And their customers would never even know. 

Nor do they need to know. Their applications would run just like they do today—without any changes.

Yet if you ask them what type of code their organization is running, chances are they will spell out their entire stack—React, Angular, Java, Python, PostgreSQL, and the names will keep flowing. No wonder 80% of technology budgets go into Keeping the Lights On (KTLO), i.e. managing legacy code that is brittle, subject to security risks, hard to scale, and very expensive to maintain.  

The cloud promised freedom from hardware, data management, and complexity. It delivered—but not at the application layer. The fact is, businesses still create, secure, and manage applications as they did pre-cloud. More than ever, they need a new approach to create, secure, and maintain their applications in the cloud.

That is exactly what the Enterprise App Cloud powered by 100% data-defined development achieves. Suddenly, all those languages—and the costs, risk, and complexity they entail—become as irrelevant to the enterprise as servers are.  And businesses can redirect all those resources to unleashing business agility instead. 

From low-code/no-code to the Enterprise App Cloud

The abstraction that makes the Enterprise App Cloud possible can be traced almost as far back as computing itself. The first basic coding languages were just shorthand—i.e. a layer of abstraction—that let developers more easily manipulate the 1’s and 0’s on which all computing depends. 

As software has become more complex, coding languages have evolved and proliferated, with new languages at higher levels of abstraction able to do evermore complex and/or highly specific functions. However, each language then requires its own runtime to translate that language back into 1s and 0s to do what they are supposed to do.

Like server management tools, an array of tools simplify coding. APIs provide an interface that hides (and translates) the code behind a data specification. Security capabilities have been consolidated around protocols that can be specified through parameters. Front-end frameworks like React create components that are pieces of JavaScript hidden behind data specs. And of course, low-code platforms enable developers to select capabilities visually, which the platform then translates into code. 

From programming languages to security protocols and APIs, these new technologies have made the work of development incrementally easier. However, the demand for evermore complex apps have outstripped their power to simplify. And so, most tech departments still spend a huge portion of their time writing, testing, securing, managing, and updating code.

III. How the Enterprise App Cloud powered by 100% data-defined development works

So how does the Enterprise App Cloud change the equation? Again, the analogy to the cloud is very apt.  

Cloud computing absorbed all the great technologies that made it easier to run on-premise data centers, packaging them all up and delivering computing as a service. The Enterprise App Cloud that is powered by 100% data-defined development does the same thing for development. It leverages all those technologies that abstract away the work of writing code. And then it goes one step further, making it possible to create sophisticated, enterprise-grade software without having to write or manage a single line of code (LOC)—ever. 

Two things make this possible: 

1. The Enterprise App Builder. First, the Enterprise App Builder unifies the entirety of an application in a single structured, data-defined definition, including everything from input fields, UI layouts, and logic/rules engines to ETLs, integrations/services, and data stores.
2. The Enterprise App Cloud Services (runtime). The runtime then ingests that data-defined definition (i.e. the sum of all an application’s components) and renders it into a fully functioning application in real time.

Of course, the Enterprise App Cloud doesn’t get rid of code altogether. Just as cloud computing still requires servers, the Enterprise App Cloud Services (runtime) is itself built with code. And the Enterprise App Cloud calls on and activates pieces of that code. 

However—and this is the important part—developers are completely shielded from that code and its machinery. Just as a cloud customer never has to worry if a particular server is working, a developer never has to worry about the code that actually renders the applications they build. That is the job of the Enterprise App Cloud.

Obviously, 100% visual configuration speeds application development. However, there is another powerful implication. Because the Enterprise App Cloud definition is entirely structured, it doesn’t matter what technologies the Enterprise App Cloud runtime calls on and activates. The application never needs to change, even when the technologies around it do (which they definitely will). 

That is to say, Enterprise App Cloud apps are, by definition, future-proof!

To understand the value of these “pure configuration” applications, it is helpful to think about the cloud. A cloud provider can swap out old servers for better, faster ones. The cloud customer gets faster, more reliable service, but they have to make zero changes to the apps they are running.  

In the same way, the Enterprise App Cloud Services (runtime) can keep incorporating the best new technologies that make applications run better and do more—but with zero changes whatsoever to the applications built in the Enterprise App Cloud. 

How the Enterprise App Cloud transcends low-code/no-code

Because the Enterprise App Cloud technology is relatively new, it is often lumped in with low-code/no-code platforms. It is true that both an Enterprise App Cloud  and low-code/no-code offer tools like visual drag-and-drop that speed and simplify software development. However, the Enterprise App Cloud is not just the next iteration of low-code development.  A look under the hood reveals how it is fundamentally different from low-code/no-code. 

Low-code/no-code platforms do not create a structured, data-defined configuration of the application. Rather, they transform each drag-and-drop specification immediately into code, often in a bespoke language that is hard for developers to understand. To compound the problem, low-code/no-code generally automates the creation of only 70-80% of the functionality enterprises require. 

So how do developers fill the gap? By writing code manually. 

The real cost of all the code that low-code/no-code—whether generated automatically or manually—lies in the tech debt it leaves behind. Essentially, you’re back on the same code treadmill that manual coding demands. Why? Because all that code needs to be packaged, deployed, rolled-back, secured, managed, and upgraded in the same old painstaking, manual, and risk-prone ways. 

Granted, some low-code/no-code providers do containerize the code and offer hosting as a new way to manage software. The problem is, containerization offers no real advantage over regular code-based software when low-code/no-code applications are deploying bespoke codebases and runtimes.

Going back to my favorite cloud-hardware analogy, low-code/no-code does the equivalent of automating the procurement of physical servers (code) to be deployed in server closets (codebase). That’s helpful if server closets are the best way to run a company, but we now know better. And that’s why most low-code/no-code is nothing but lipstick on legacy code.

IV. How 100% data-defined development accelerates time-to-market (and that’s just the beginning) 

As we have seen, the Enterprise App Cloud that is powered by 100% data-defined development completely abstracts away all code from the software development process, not just 70-80% of it like most low-code/no-code platforms. As a result, the entire software development process becomes 100% visual and configurable. 

In addition, it turns individual components of an application into a structured, data-defined atomic unit. As a result, these units can then be composed into reusable microservices and other higher-level application functionality. Separating configurations from code means that the Enterprise App Cloud provider can easily and efficiently handle all the mundane tasks that can add up to crushing tech debt over the course of the entire SDLC (a benefit we cover more fully in the next section). 

Not surprisingly, organizations can typically create apps 3X faster—and as much as 10X faster—with the Enterprise App Cloud vs. low-code/no-code. This approach also makes everyone involved in the process of application development more productive. To understand why, consider how the Enterprise App Cloud transforms the way everyone involved—business users, newbie developers, and seasoned engineers—does their job. 

Benefits for business users 

By making development entirely visual (think Visio), business users can: 

• Actively participate in development by following the process visually, rather than handoff requirements to the tech team.

• Build straight-forward applications themselves and add/change functionality, while tech teams can ensure all necessary guardrails are in place.

Benefits for new developers 

People new to development can begin composing complex enterprise-grade applications within weeks, because the Enterprise App Cloud:

• Doesn’t require learning a new coding language.

• Makes building workflows and apps entirely visual, including integrations and data management.

Benefits for seasoned engineers

By eliminating the hard work of manual coding, seasoned developers can focus on high-level functions like:

• Quality control

• Security and governance

• Management of mission-critical legacy systems

V. How the Enterprise App Cloud removes friction from the entire SDLC

While the Enterprise App Cloud speeds and simplifies development, it is the value it brings across the software development life cycle that makes it a truly transformational technology. And again, its power to do so begins with the fact that  applications built in the Enterprise App Cloud are really only configuration files—100% structured data rather than unstructured, language-based code. 

As a result, the Enterprise App Cloud provider can take care of 100% of the underlying code—along with the security, compliance, and upgradeability related to it. And that means organizations can focus precious talent and budget on innovation instead of managing (and paying down) tech debt. 

To understand the power of the Enterprise App Cloud to eliminate tech debt, let’s first consider traditional development methods, including low-code/no-code, in which apps are not configurations calling code but consist of code themselves, whether those lines of code (LOCs) are manually or automatically generated.  

Every codebase you use requires its own runtime—the equivalent of a server-closet in the pre-cloud days. Like server-closets, each codebase requires a separate lock and a security guard to keep hackers away, plus cameras and sensors to monitor activity and an HVAC system to make sure things don’t overheat. 

In other words, each new runtime introduces a whole new set of problems and risks. And yet, enterprises typically run hundreds, even thousands, of codebases—a true security, scalability, and maintenance nightmare. 

To make things even worse, those codebases often include exactly the same set of functionality, and therefore a fresh set of LOCs that need to be managed. When you need to upgrade or security-patch a functionality, you need to do it individually across all those codebases, and then redeploy them one by one. 

None of that is necessary with the Enterprise App Cloud. You have only one runtime that runs on one codebase, providing the cloud-like mega-scale that enterprises need. Each application has its specific configurations, but all run on the same codebase that can be secured, monitored, and maintained at scale. Here are just a few of the benefits:

Speed to insights

Every IT organization must answer a number of critical questions about the apps it runs. How many potential vulnerabilities does it have? Are the roles set up properly? Does it have the optimal architecture? Does it create bottlenecks? What is the distribution of functionality that it uses? 

Because applications built in an Enterprise App Cloud are just configurations that run on a single code base, it is far easier to build a control tower that can answer these questions instantly. That is why these apps typically have 100x fewer bugs and architectural defects than traditional apps.

Reduced TCO 

By decoupling the Enterprise App Cloud from the runtime that executes it, that runtime can be optimized, upgraded, and scaled as new technologies come online. And yet the definition of the application never has to change! As a result, applications can always run on the latest and greatest technologies. 

Equally important, an Enterprise App Cloud powered by 100% data-defined development only requires one runtime across all applications. This enables scalability, reusability, security, and efficiencies that low-code/no-code could never match. Not surprisingly, the total cost of ownership (TCO) of applications is typically 65% lower than traditional apps.

Reducing tech debt across the SDLC

These benefits may sound abstract. To bring them alive, let’s take a look at all the tasks the Enterprise App Cloud takes off your plate across the SDLC. 

Infrastructure planning & management

• No need to purchase or manage servers

• No dependencies to install 

• No DNS to configure or URLs to hook up

• No manual management of scalability or availability

UI/Application development

• No need to need to master HTML/Javascript (or any code)

• No need to connect fields to databases

• No need to manually implement validations

• No need to manually build validation displays

Integrations 

• No need to understand how to make requests or find libraries, codes, etc. 

• No need to create secure store for credentials

• No need to manually build out logic of multiple authentication types

Database management

• No need to set up databases or establish connectivity

• No need to run commands to create or alter tables

• No queries to write

• No time or effort to scale or manage availability

Security

• No manual setup of secure user authentication 

• No manual setup of secure data storage and encryption 

• No manual setup for resiliency against cyber attacks

Deployment 

• One-click deployments and rollbacks

• No broken builds

• No time spent on managing builds

Upgrades

• Only upgrade your business logic

• No code changes when upgrading applications

• No need to upgrade underlying tech as it evolves

VI. Your accelerated path from low-code/no-code to the Enterprise App Cloud

We truly believe the inherent advantages of an Enterprise App Cloud powered by 100% data-defined development are so great that it will become as ubiquitous as cloud computing. However, Unqork currently offers the only solution of its kind. 

And this is not speculative technology or a proof of concept (POC). Many of the world’s leading companies use Unqork for many of their most important software projects, including BlackRock, Marsh, Goldman Sachs, New York City, and more. And they trust Unqork because it is engineered from the ground up to handle the demands of the most complex and highly regulated industries, including financial services, insurance, health care, and the public sector. 

Yes, development with the Enterprise App Cloud is fast. So is the process of integrating the technology into your organization. With no bespoke (or in fact any) languages to learn, new developers and even tech-savvy business users can start building applications in just a few weeks. And as a cloud offering, Unqork requires no changes whatsoever to your current IT stack. Your entire organization can be up and running in no time. 

Want to learn more? Take the guided tour below.