Seamless machine learning solutions make teams more agile
Artificial intelligence and machine learning technology are changing the way we create software. Engineers and developers can automate tasks that used to require manual input, saving a significant amount of time in the race to market. As technology advances, customers expect more AI-driven features, from text editing to asset creation and beyond. Being on the cutting edge of this technology helps you meet those expectations and deliver a superior solution.
The problem? Utilizing AI and machine learning technology requires a significant amount of work and technical expertise if you’re building a platform from scratch. The solution: Partnering with a low-code/no-code AI and machine learning platform. This way, your team can access a plethora of automated tools without extensive coding knowledge. Here’s how a no-code/low-code AI platform can streamline your workflows — and what to look for in such a platform.
What Is a Low-Code/No-Code AI and Machine Learning Platform?
Low-code/no-code platforms allow developers and engineers to create software applications without having to write extensive code. Low-code platforms require very little manual coding and often use automatically generated code, while no-code platforms eschew the need for writing code entirely. Instead, they utilize intuitive templates and menus that make it easier for developers to build programs from scratch.
Low-code/no-code platforms are becoming increasingly popular because they allow developers to deploy applications significantly faster — in some cases up to ten times as quickly. To learn more about how no-code/low-code platforms speed up development with intelligent automation, read our white paper.
Understanding the Role of Low-Code Machine Learning
Though the phrases are often used interchangeably, AI and machine learning aren’t quite the same. AI is a broad term that refers to any technology that allows machines to simulate human thought. Machine learning is more specific: It allows computers to identify patterns based on human input and adapt accordingly.
One example of how machine learning works is the “Captcha” visual puzzles that websites often ask visitors to solve before logging in. While you’re simply trying to prove you’re a human, you’re actually training these Captcha systems and making them more effective.
Features to Prioritize in Low-Code/No-Code AI and Machine Learning Platforms
Streamlined AI Workflows
Automation plays a major role in the modern software development landscape, and the ability to create intuitive AI workflows makes it even more productive. For example, Retool’s AI platform allows developers to “chain together business logic, data connectors, and dynamic prompts to automate hundreds of manual tasks.” Similarly, DuploCloud uses AI and machine learning pipelines to enable more efficient operations. This is arguably the most important function of a no-code/low-code machine learning platform.
Seamless Integrations
Another function of no-code/low-code AI platforms is the ability to integrate tools like the LLMs discussed above. This includes ChatGPT and other AI chatbots, image generators like Adobe Firefly, and many more. Rather than having to build similar tools from scratch, developers can tap into powerful machine learning that’s already been trained on a wealth of data.
Built-in Compliance Checks
There’s no question that AI plays a role in the modern software ecosystem, but it’s not something that can be left to run on its own. You’ll still have to meet your industry’s legal regulations, standards, and other guidelines even as you automate more and more steps in your pipeline. To ensure nothing slips through the cracks, choose an AI/machine learning partner with built-in compliance checks. This will significantly reduce the risk of non-compliance issues.
Real-Time Monitoring
Streamlining your AI workflows makes operations more efficient, but what if something isn’t working? Without real-time monitoring, you might not notice any setbacks right away. This can cause costly performance issues that can increase time to market. Look for platforms that provide real-time insights into how all your systems are performing. This way, you can solve any issues that arise quickly and get back to business.
Continuous Integration and Deployment
Deployment frequency is one of the most important metrics in DevOps. A higher deployment frequency indicates that development is running smoothly, while a lower one shows that there’s friction in the process. Continuous integration and continuous deployment (CI/CD) pipelines automate building and testing procedures while allowing developers to deploy code changes more regularly. In DuploCloud’s case, building continuous integration and deployment into the platform makes it easier for our partners to integrate third-party solutions like GitLab CI/CD, Katkit, and more.
Master AI and Machine Learning with DuploCloud
If you’re ready to deploy AI and machine learning workloads and see what advantages AI can offer, DuploCloud can help. DuploCloud’s no-code/low-code platform democratizes DevOps with automated provisioning, smart integrations, compliance and security checks.
By leveraging Infrastructure as Code, DuploCloud automates your own infrastructure setup while making management, replication, and scaling more efficient. To learn more, get in touch and set up a demo.
