Low-code and no-code platforms are revolutionizing the development of applications, websites, mobile apps, forms, dashboards, data pipelines, and integrations. No-code platforms empower business users or citizen developers to move away from spreadsheets, enhance email collaborations, and transition from manual tasks to automated tools across departments. Low-code platforms cater to technologists, offering streamlined ways to deliver and support software with minimal coding.
Gordon Allott, President and CEO of K3, explains that low code is essentially abstraction, simplifying the user experience by removing non-essential elements.
Low- and no-code platform providers are expanding their focus beyond applications and automation into emerging areas such as AI and machine learning. The lines between business workflow platforms, AI tools, and low- and no-code platforms are becoming increasingly blurred.
This article looks at examples of businesses utilizing low- and no-code technologies to deploy AI and machine learning capabilities, and also discusses the insights of tech executives on the use of such tools.
TABLE OF CONTENTS
- AI capabilities in SaaS tools
- AI in no-code workflow tools
- Low-code integrations with ML
- Low-code AI search and IoT
- Conclusion
AI capabilities in SaaS tools AI is being used in a variety of tools, such as ChatGPT, Jasper.ai, AI video creation tools, image recognition software, and chatbot platforms. However, while many SaaS tools feature AI capabilities, most do not qualify as no-code.
AI in no-code workflow tools AI and no-code tools have a history of being used together in information extraction from documents, a process that typically involves a combination of data processing, machine learning, and workflow automation. NLP Lab, a no-code text annotation tool by John Snow Labs, is employed in healthcare to incorporate the expertise of clinical specialists into machine learning models.
Low-code integrations with ML No-code and low-code platforms are integrating AI and machine learning capabilities to facilitate experimentation and streamline the implementation of ML models in production use cases. Microsoft’s AI Builder service, part of the Power Platform, offers over 10 prebuilt AI models for tasks such as text recognition, entity extraction, and sentiment analysis.
Low-code AI search and IoT Low-code AI search and IoT are two examples of SaaS platforms with low-code or no-code development options and AI capabilities. These platforms are helping businesses use IoT and AI for smart buildings, manufacturing, and agriculture use cases, among others.
Conclusion As more companies look to experiment with AI, they will seek development options that accelerate delivery and reduce the required expertise. Tools that integrate AI capabilities with no-code and low-code development options will become increasingly attractive, particularly for businesses without in-house data scientists and software developers.