With AI, the extent and benefits of low-code capabilities become further supercharged: OutSystems

Pradeep Chakraborty
New Update

OutSystems, founded in 2001 in Lisbon, Portugal, is a low-code development platform, which provides tools for companies to develop, deploy and manage omnichannel enterprise applications. 


Naveen Kumar Kalyankar, Regional VP India, OutSystems, tells us more. Excerpts from an interview: 

DQ: How can low-code and AI coexist? 

Naveen Kumar Kalyankar: The integration of AI in low-code platforms is not a new phenomenon. However, the greater accessibility and growth of generative AI has facilitated the ease of developing more intelligent enterprise applications. The combination of AI and high-performance low-code has the capacity to address and improve every phase of the software lifecycle, spanning from frontend UX design to back-end data integration and performance. This collaboration yields significant advantages for enterprises across diverse industries.


On its own, high-performance low-code enables enterprises to create mission-critical applications faster and easier than traditional methods. This is by offering a visual drag-and-drop interface that radically simplifies coding processes, making it accessible to non-developers, business users, and developers alike. With AI, the extent and benefits of low-code capabilities become further supercharged. 

For example, low-code platforms that incorporate generative AI can feature app generation using conversational prompts and AI-powered app editors that offer intelligent coding suggestions. Such platforms can also offer tools which leverage machine learning to provide expert-level assistance in areas such as complex software builds, code validation, reducing technical debt and vulnerability checks. 

This dynamic synergy between AI and low-code equips businesses with the ability to swiftly revolutionize their operations and maintain a consistent pace of innovation. This not only empowers them to create high-quality applications and promptly adapt to evolving customer needs but also facilitates the expansion of their user base in a fiercely competitive market. 


DQ: How can low-code lower the barrier to bespoke AI? 

Naveen Kumar Kalyankar: Low-code platforms play a pivotal role in lowering the barrier to bespoke AI application development through a holistic, multifaceted approach. However, 22% of employees in the Asia Pacific express a lack of confidence in their ability to acquire new AI-related skills, even though 41% believe AI can enhance productivity and efficiency at work.

High-performance low-code platforms address this challenge by simplifying complex coding processes that often come with developing, running and maintaining complex AI applications. These platforms can offer pre-built AI components that allow organisations to effectively build a range of AI-powered business functions. 


This can include Q&A chatbots for customer satisfaction, extracting information from internal documents to shorten processing time, or determining customer satisfaction with language sentiment analysis. 

By being able to incorporate advanced AI features without starting from scratch, individuals with varying technical expertise can create AI applications even without extensive coding knowledge. Consequently, business teams and subject matter experts can also actively participate in the AI application development process, and contribute relevant insights to build AI applications that best suit evolving business needs. 

The accelerated development process enabled by low-code platforms, coupled with reusable components and pre-built templates, also facilitates rapid prototyping and iteration, reducing the time and effort required to bring world-class AI solutions to fruition.


Overall, low-code platforms democratize the development of AI applications, making it more accessible, efficient, and collaborative for organizations aiming to harness the power of bespoke AI solutions.


DQ: What are the end benefits of democratized AI with low-code?

Naveen Kumar Kalyankar: Democratized AI with low-code brings forth a host of end benefits that contribute to the widespread adoption and successful implementation of artificial intelligence within various organizations. 

Firstly, by enhancing application development with AI-augmented low-code, accessibility is significantly enhanced, allowing individuals across diverse roles, even those without extensive coding backgrounds to actively participate in application development. This democratization not only broadens the pool of contributors but also facilitates better collaboration between domain experts and IT professionals, allowing back-end processes to become more inclusive and efficient.


Speed and agility in application development are also markedly improved. Low-code platforms enable rapid prototyping, iteration, and deployment, shortening the time it takes to deliver not just enterprise applications, but also complex applications with AI functions. This agility is crucial in adapting to rapidly changing business landscapes and customer needs. 

Cost-effectiveness is another notable benefit. By lowering the technical barriers to entry, organizations can leverage existing talent pools more effectively, reducing the need for specialized AI developers. This democratized approach also minimizes the resources required for training and recruitment. 

Ultimately, democratized AI with low-code fosters innovation, fostering greater accessibility when it comes to building key business functions,  driving organizational growth and competitiveness in the evolving landscape of artificial intelligence.


DQ: How is OutSystems’ use of AI in app development a game-changer across verticals? 

Naveen Kumar Kalyankar: Prior to the widespread adoption of generative AI, OutSystems has already been working to integrate AI into its solutions. The OutSystems AI Mentor System offers a suite of analysis tools that use machine learning to provide expert-level assistance across crucial aspects of the software development lifecycle. 

These tools include dedicated mentors guiding developers through complex builds, ensuring code integrity, intelligently checking for vulnerabilities, assessing peak performance potential, and scanning app portfolios to minimize technical debt. 

Additionally, OutSystems brings the power of AI into enterprise business functions, helping businesses to rapidly develop multidimensional chatbots, custom AI models, and conduct document processing and sentiment analysis.  This addresses knowledge gaps, enabling developers to expand portfolios without incurring technical debt, while maintaining optimal performance, security, architecture and UX. These rich components ultimately minimize the amount of glue code while also reducing the complexity of implementing a complete use case from end-to-end. 

Last year, the company introduced Project Morpheus, a new generative AI solution that aims to enhance the speed and simplicity of development. The solution will allow enterprises across industries to generate instant apps through conversational prompts, tap on an AI-powered app editor to provide full-stack suggestions, from data to UI, and access real-time visual representations of app modifications, empowering junior developers and non-coders to build highly adaptive app experiences.

Moreover, businesses can already leverage low-code to swiftly create their AI applications or redefine operations with AI by utilizing an extensive system of connectors to popular services from Microsoft, Google, Amazon, and other third-party providers. This also includes a connector for ChatGPT that makes it easy to harness the power of generative AI within their applications, expand into new use cases and unlock new possibilities.  

DQ: What are the trends and future potential of low-code technology?

Naveen Kumar Kalyankar: With the global market revenue for low-code or no-code technologies expected to reach US$21 billion in 2026, high-performance low-code will continue to transform business innovation by leveraging automation, AI-assisted development, and enterprise-level reusability. 

The growing adoption of AI in enterprise technology means many low-code platforms will likely reposition themselves as tools for AI-powered application development. With this, there will be a greater emphasis on the role of the developer to balance the delegation of routine tasks to AI-powered low-code solutions, with the ability to take on higher-level innovation and application design. 

Furthermore, low-code tools are expected to be central in enabling organisations to construct AI applications from the ground up in the coming years. With a greater ease of integrating large language model connectors, developers and organizations will be able to tap on low-code to harness generative AI for virtual assistants and personalized user recommendations. 

Looking ahead, we will continue to see immense potential in the synergy between AI and low-code for innovative and strategic use cases. This synergy will ultimately be key in helping organisations build applications with power, speed, scale and security needed to differentiate themselves in an evolving global market. 

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