When a company plans to acquire software, the first decision is whether to buy off-the-shelf software, rent a solution, or opt for custom development. Companies typically choose custom development when they have specific business needs that are not adequately met by standard solutions or when they seek a competitive edge by not using the same software as their competitors. Custom development is often favored for the greater freedom it offers in user experience, branding, scalability, performance, data security, regulatory compliance, and integration. Moreover, custom solutions allow companies more control over the application’s lifecycle, enabling better influence over ongoing support and future enhancements. While custom software may involve higher initial costs, it often proves more cost-effective in the long run, especially if off-the-shelf solutions require extensive customization, leading to high maintenance expenses.
Once a company opts for a custom solution, the next step is to choose the appropriate development approach. In addition to traditional custom development, low-code and no-code platforms are now available, as well as AI-supported development tools. An increasingly popular option is a hybrid approach that combines the strengths of these different methods: the Custom Application Building Platform.
Traditional Custom Development
Custom development is often perceived as a process where every line of code is meticulously crafted by developers from scratch. However, this is no longer the case. Even in custom development projects, we leverage a significant amount of pre-built and generated code, as well as components that rely on modeling rather than manual coding. For instance, popular front-end frameworks like Angular or React allow developers to build screens using pre-made, complex elements. On the back end, tools like Spring enable the implementation of security features through simple configuration. Libraries such as Hibernate simplify database access, while tools like Apache CXF generate client code for web services. Process automation tools like Camunda allow developers to create process models that the application can execute. While it’s challenging to quantify the exact amount of time saved by these tools, experience suggests they can reduce the required code by 10-20%, and with optimal use, this can reach 30-40%.
Advantages and Disadvantages
The undeniable advantage of custom development is the full control it offers over architecture, technology, and integration. This approach allows for a high degree of customization, enabling the implementation of almost any specific requirement within reasonable financial and time constraints. It is also ideal for flexibility, as the application can adapt to the company’s evolving needs throughout its lifecycle. However, this flexibility comes at a cost: managing time and expenses can be challenging, and the quality of the software can vary depending on the expertise and experience of the development team.
Low-Code/No-Code-Based Custom Development
Low-code and no-code platforms aim to provide the tools needed for application development within a unified, predominantly visual interface, making them accessible even to users with IT affinity but without extensive coding knowledge or experience. These platforms integrate the application architecture, technologies, and components into a single environment, freeing developers from design concerns. They offer pre-built, ready-to-use functionalities such as code libraries and connectors for easy integration with popular enterprise applications like SAP. Data management, process automation, and user interface design are made achievable through modeling and configuration, with code generators often working in the background. These platforms also come with built-in security features, debugging and testing tools, and they simplify deployment across different environments.
Developers can insert custom code at specific points to handle cases that modeling and configuration do not fully cover. While there’s no precise measurement of how much coding is required, experience suggests that with a low-code platform, up to 80% of an application can be realized through modeling and configuration, with custom coding accounting for about 20%. The proportion of custom development depends on how effectively the platform’s capabilities are utilized. In no-code platforms, the need for custom coding can be reduced even further with optimal use of the platform’s features.
Advantages and Disadvantages
One of the greatest advantages of low-code/no-code platforms is their ability to significantly shorten implementation time by reducing the need for custom coding. The use of models, such as flowcharts, facilitates effective communication between business and IT stakeholders. A large portion of the application is built from proven and tested code, resulting in fewer errors and better quality. The platforms offer a clear, well-documented structure, making them easy to learn and use for building applications.
However, modeling and configuration also impose certain limitations, as the scope of models and parameters is well-defined. Implementing anything beyond these bounds can be challenging. Furthermore, these platforms are typically closed-source licensed products, with development directions determined by the vendor, leading to a degree of dependency. Since they are designed to be broadly applicable, they may not always meet specific performance requirements.
AI-Supported Custom Developments
AI Copilot tools can significantly enhance developer efficiency without requiring changes to development processes or technologies. These tools assist not only by completing the lines of code being written but also by generating larger code units, such as the entire logic of a well-named function. They provide substantial support in code review, optimization, and refactoring. AI tools drastically reduce the time needed to locate errors and offer valuable suggestions for solutions. They quickly become indispensable in automated test generation, creating test cases for the code. Another strength is their ability to work as a “virtual pair” with developers, providing real-time suggestions during coding. This support is particularly valuable when dealing with familiar codebases or technology stacks but becomes even more crucial in unfamiliar environments. While it’s difficult to quantify the productivity boost, industry data suggests it can easily reach 10-20% and, in some cases, even 30-40%. Moreover, AI tools support not just developers but also testers, business analysts, and project managers.
Advantages and Disadvantages
Using AI tools quickly leads to efficiency gains while also improving code quality. For junior developers, AI provides significant assistance, accelerating the learning process, while for experienced developers, it supports solving more complex problems and exploring unfamiliar areas. However, it is important to remember that creativity and innovation remain human tasks, as AI works only with the data and patterns it has access to.
Certain companies may face data protection and security risks with AI usage, which could even prevent its application. Additionally, AI tools may reach their limits in more complex, specialized environments where they cannot provide optimal support. For example, in a low-code/no-code platform, AI might offer less support than in custom development, where it has full visibility of the codebase.
Custom Application Building Platform
A CThe Custom Application Building Platform aims to provide the toolset required for application development as an integrated system optimized for developers. The platform offers an application framework that defines the application’s architecture and technologies while providing essential services for integrating various application capabilities and business functions. Developers can add capabilities such as process automation to create business functions.
The platform includes many pre-built functions and integrations and supports the easy management of data, processes, and user interfaces. Throughout the development process, the platform aids developers with code generation. Security features, debugging, testing, and deployment support are also built-in. AI support is particularly effective, as the Copilot has access to the entire codebase, providing maximum assistance during development.
Clients do not need to own the platform as they receive the necessary parts along with the completed application. The pre-built building blocks are not only configurable but can also be modified to meet unique requirements.
In essence, this platform elevates the custom development toolkit to a new level, building on the principles of low-code/no-code platforms and incorporating AI support. While it is difficult to determine the exact increase in productivity, it certainly surpasses traditional custom development, though it only approaches but does not fully reach the efficiency of low-code/no-code platforms.
Advantages and Disadvantages
Berries Custom Application Building Platforms approach the level of custom applications in terms of customization and flexibility, as developers have full control over the codebase. While the platform approach significantly shortens development time, it does not match the speed offered by low-code/no-code platforms. Managing time and costs is easier than in traditional custom development, but due to the high degree of freedom that allows customization of any part of the code, developers need to work thoughtfully.
The high proportion of reused code improves quality, as these components are already proven and tested solutions. Since these platforms are available as a service and are built by development companies themselves, there can be significant differences in the quality and capabilities of the platforms. Therefore, careful consideration is needed when selecting a development partner to ensure the right platform and support during the project.
The Renaissance of Custom Development?
The last major productivity boost in the world of business software came with the advent and spread of Java more than 20 years ago. Since then, the industry has tried various methodological improvements, but none have brought breakthrough success. The rise of functional programming languages was also followed with high hopes, but due to the steep learning curve and high resource demands, the breakthrough did not materialize. Recently, the promising potential of low-code/no-code platforms has come to the fore, and we are witnessing their rapid rise. More recently, artificial intelligence has explosively entered the development world, gaining increasing ground.
While the industry has experimented with various methods to boost productivity, custom software has started to take a back seat. This is partly due to the proliferation of packaged solutions that have satisfied a wide range of needs and partly because of the hassle and risk associated with custom development. However, a new direction is now emerging from the synergy of past efforts, building on the foundations of custom development while combining the principles of low-code/no-code and AI support. This approach may bring custom software back to the forefront.
It is likely that in the coming period, the proportion of custom software will increase as companies will again be more willing and daring to commission custom solutions.
