Low-code and No-code AI Platforms are new tools that make using AI easier for businesses. They help companies without advanced technical skills to use AI for different tasks like improving customer service and making internal processes run smoother.
Top 10 Best Low-Code and No-Code AI Platforms Examples
This is why the emergence of a brand new generation of no-code and low-code AI platforms and tools is so interesting. From designing web services to coordinating sales and marketing campaigns, it’s easier than ever to get started with AI. Here in this article, you will learn about the top 10 best Low-Code and No-Code AI Platforms examples and what they mean.
List of Top 10 Best Low-Code and No-Code AI Platforms
What is Low Code/No Code AI Platform ?
Low-code and no-code are ways to make apps quickly without needing much or any coding skills. They let people who aren’t tech experts build their own solutions, which helps free up tech teams for more complex work.
No-code is the simplest of the two. It lets you create basic apps easily using a visual, drag-and-drop method. However, it’s not great for overhauling old systems, speeding things up a lot, or connecting different systems. It’s best for small, specific projects within a team. The ease and simplicity of no-code are both its strengths and weaknesses. You can’t change it much because it’s mostly pre-built by its creators.
Low-code is more flexible, sitting between no-code and full coding. Like no-code, it uses a visual, drag-and-drop approach, but it also lets you add your own coding. This gives developers a balance, allowing them to work faster without starting from scratch every time. Low-code platforms can handle bigger projects, connect with other systems, and work either in the cloud or on your own servers.
Best Low-Code and No-Code AI Platforms Examples
Here’s an outline of some of the tools in the marketplace that aim to open up the AI revolution to everyone. Some of those are designed for people without any experience in any way, while others are most beneficial for those who already have a background in machine learning, but need to lessen the tedious and recurring detail concerned with preparing data and designing algorithms.
1. Akkio
With Akiko, you can install AI in 10 minutes without coding or data science experience. It permits the development of AI-powered workflows to install and evaluate them rapidly. It additionally has strong integrations, including industry-standard data systems, which include Snowflake, and advertising tools, such as Hubspot and Salesforce.
Features:
- Deploy AI in 10 minutes without coding.
- Development of AI-powered workflows.
- Rapid deployment and evaluation of workflows.
- Integrations with Snowflake, Hubspot, Salesforce, and so on.
- No coding experience is required.
Pros:
- Quick and easy AI deployment.
- It has many use cases for different industries like sales forecasting, lead scoring, fraud prevention, etc.
- Suitable for customers without coding or data science expertise.
Cons:
- It may lack some superior features for complex tasks.
- It has limited customization for highly specialized workflows.
- It may lack some level of support as other platforms.
Link: https://www.Akkio.com/
2. DataRobot
A cloud-based platform with tools for automating data preparation, growing, and deploying algorithms. It consists of dedicated models for business use cases, including banking and retail, healthcare, production, and public sector businesses. One fascinating characteristic is its emphasis on explainable AI, which seeks to introduce trust within the insights and selections it generates by making its strategies understandable to humans.
Features:
- A cloud-based platform for automating data preparation.
- Develop and set up algorithms for diverse business use cases.
- Emphasis on explainable AI for generating trustworthy insights.
- Tools for banking, retail, healthcare, manufacturing, and so on.
- Automation of machine learning model development.
Pros:
- It has expert technical support.
- User-friendly interface with simple version control and data preparation.
- Accurate reports of data examination and model development.
Cons:
- It has a steeper learning curve for beginners.
- Limited customization in comparison to extra-flexible structures.
- The pricing version may not be suitable for small budgets.
3. GeneXus
GeneXus is a low-code business platform that employs artificial intelligence (AI) to automate and maintain programs across all structures, coding environments, and devices. The tool is meant to provide flexibility, high performance, and creative freedom for the user.
GeneXus can help a company application and its accompanying multi-channel user experience substantially. It combines Generate AI, an AI assistant, with code generators to simplify your software program development technique. The AI will continuously suggest new lines of code based on your type of program and what you want to develop.
Features:
- A low-code enterprise platform with AI automation.
- Combine Generate AI and Code Generators for development.
- Flexible software development with high performance.
- The AI assistant shows new lines of code, saving time.
- Multi-channel consumer experience and app maintenance.
Pros:
- Constant improvement to the latest security measures.
- Supports multiple platforms including web, mobile, cloud, etc.
- It saves time because of its faster coding capabilities.
Cons:
- Ineffective troubleshooting tools which makes bug fixing difficult.
- Inefficient customer service.
- Limited documentation in comparison to sizable platforms.
4. Lobe
Lobe is a simple image recognition algorithm schooling tool. Microsoft created this low-code artificial intelligence system to assist users in learning the fundamentals with a platform that automatically selects the models that are most likely to succeed based on the person’s workload. There isn’t any coding required, and you may quickly upgrade to Azure AI, Microsoft’s superior ML model, at any time.
Features:
- Simple image recognition algorithm training devices.
- Created by Microsoft for basic AI mastering.
- Automatically selects models based on workload.
- No coding is required for model training.
- You can upgrade to Azure AI for advanced system mastering.
Pros:
- Simplifies image recognition algorithm training.
- It is free and easy to use.
- Allows you to export your model to different formats like TensorFlow, Core ML, etc.
Cons:
- It only supports image classification.
- It requires a powerful computer to run smoothly.
- Does not offer a lot of customization or control over the machine learning process.
Link: https://www.lobe.ai/
5. Nanonets
You can use this low-code computer vision platform to automate extracting structured or semi-structured data from imported files. If your company spends time and money on expensive and time-consuming procedures, which include uploading records from paperwork, text files, etc., this could be exactly what you’re looking for. Thanks to its use of machine learning, it learns from its mistakes and will become more accurate at locating the data you need.
Features:
- Automates extracting structured or semi-structured information.
- Low-code computer vision platform.
- Machine learning for improved accuracy.
- Efficient in handling records from forms and text files.
- It learns from mistakes, improving information extraction.
Pros:
- It supports multiple platforms for extracting data such as email, SAP, etc.
- Improved accuracy over time via machine learning.
- Perfect for businesses handling structured data extraction.
Cons:
- It may not extract the data accurately from complex documents.
- It may not protect your privacy or information.
- There is limited support for languages.
Link: https://nanonets.com/
6. Obviously AI
Obviously AI platforms can carry out data prediction within one minute without making customers write a single line of code. To be more particular, you need to design and install the machine learning algorithm (of course, without coding), and the platform will automatically run based on your custom-designed machine. Because of this, this low-code AI machine learning platform is suitable for everybody, without or with AI and coding experience.
Features:
- Data prediction within one minute without coding.
- Design and setup of machine learning models without coding.
- Leverage data logs to shape the database without code.
- Share machine learning models privately or publicly.
- Integration of CSV documents with data resources.
Pros:
- Fast data prediction without coding saves time and money.
- It has state-of-the-art models with high speed and accuracy.
- Quick and smooth integration with other tools and apps.
Cons:
- Limited security and privacy measures.
- May lack capabilities for enormously complex or custom tasks.
- May not be compatible with some data formats or sources.
7. Pega
Pega’s smart engine is changing the world of automation. This low-code AI platform not only helps businesses build applications quickly with little effort on coding but also brings effective AI packages with data mining, predictive analytics, language, and event processing. These capabilities will ensure strong computerized software that aids you in each decision with accuracy.
Features:
- An intuitive drag-and-drop interface for building programs.
- Visual models and business policies for outlining good logic.
- End-to-end business system and workflow management.
- AI and machine learning capabilities for smart decisions.
- Responsive and native mobile application development.
Pros:
- An intuitive interface for non-coders.
- A 30-day trial is available.
- AI and machine learning for decision-making.
Cons:
- The basic plan starts off at $35 per user/month.
- There may be a learning curve for complex workflows.
- Limited customization for some use cases.
Link: https://www.pega.com/
8. PyCaret
This Python library might require additional technical knowledge as compared to a number of the other tools indexed here. However, it’s nevertheless considered low-code because it provides some pre-configured features and wrappers that greatly simplify the tasks of data preparation, analytics, and model training.
Features:
- Python library for low-code AI.
- Pre-configured capabilities for statistical guidance and analytics.
- Wrappers to simplify version training responsibilities.
- Requires extra technical knowledge.
- Suitable for data scientists, and analysts.
Pros:
- Simplifies tasks for data preparation and analytics.
- Provides pre-configured features for faster development.
- Flexibility for uses with Python and technical information.
Cons:
- Requires additional technical understanding.
- It may not be appropriate for users without Python skills.
- Limited features in comparison to other more advanced libraries.
Link: https://pycaret.org/
9. SuperAnnotate
Big companies with large databases would require an end-to-end platform that can annotate, control, and version ground truth data for their AI model, for this SuperAnnotate is the best choice. This specialized low-code computer vision and prescient platform offers a full-fledged toolset and an effective data management system that can annotate and extract meaningful insights from various digital inputs. From there, you may easily orchestrate your AI pipeline, scale it, or automate it 3x-5x quicker.
Features:
- Annotation of video, text, and pictures with high throughput.
- Customized workflow setup and consolidation of pipelines.
- Automation functions for scaling and automating AI pipelines.
- Multi-level collaboration with access management tools.
- Specialized low-code computer vision platform.
Pros:
- It is a powerful record-control system.
- 3x-5x faster AI pipeline scaling and automation.
- Suitable for massive businesses with great databases.
Cons:
- A specific focus on massive firms.
- It may be complex for smaller projects.
- Limited flexibility or customization for non-vision-related responsibilities.
10. Teachable Machine
Teachable Machine offers simple, straightforward tutorials that can guide you through the technique of training algorithms to categorize and classify data, one of the most simple use cases for ML and AI. The most beneficial feature is a training device for learning the basics.
Features:
- Provides easy tutorials for algorithm training.
- Guides users via the class system.
- Basic use cases for ML and AI.
- Fundamental teaching tools for mastering AI fundamentals.
- No coding is required for basic model training.
Pros:
- It is easy to learn, fast, and accessible to everyone.
- Suitable for customers new to ML and AI.
- It supports inputs such as sounds, poses, and images.
Cons:
- Limited to simple-use cases.
- May not provide advanced features for complex tasks.
- May not be compatible with some devices or browsers.
Best Low-Code/No-Code Platform
There is no single “best” low-code or no-code AI platform, as each platform has its very own unique functions and capabilities that cater to unique consumer needs and technical knowledge levels. The no-code machine learning systems landscape will continue to conform and improve, making ML more accessible to a wider range of users. Choosing the best no-code machine learning platform is an important choice, and it’s vital to carefully select the tools and platforms that you use.
Features of Low Code/No Code AI
Low-code and no-code platforms reduce coding complexity via pre-configured templates and visual interfaces. Some of the capabilities of using those structures are:
- Broader usability: Low-code and no-code systems are constructed to empower all users, irrespective of their technical expertise. Hence, people without coding experience can quickly build sites and applications. And if you have some coding talents, you may add your code and personalize an app or website online.
- Faster code generation: Writing code line by line takes a whole lot of time, which increases when you have restrained coding abilities. Using a low-code or no-code platform will help you create code quicker to increase and set up software programs quickly.
- Cost-effective: Writing code manually involves more investment in developers, time, resources, infrastructure, and preservation. Low-code or no-code platforms decrease your funding for these aspects and enhance ROI.
Apart from the above, those systems allow higher collaboration among the IT and business teams, increase understanding, and help you collect client reviews quickly with easy-to-construct prototypes.
Also Check –
- Top 10 No-Code Development Platforms
- Best No-Code Tools for Developers in 2024
- Differences between Low-Code and No-Code Development
- Difference between Low Code Software Development and Traditional Software Development
Conclusion
The era of low-code and no-code platforms has ushered in a new era of innovation, permitting individuals from various backgrounds to create excellent digital products. Whether you’re an experienced developer or someone taking their first steps into the digital world, these best Low-Code and No-Code AI Platforms provide a varied range of options.
As you embrace these empowering platforms, you will witness the democratization of app development – a movement that encourages creativity, fosters innovation, and opens doorways for a much wider selection of people to bring their ideas to existence in the digital world.
Best Low-Code and No-Code AI Platforms Examples- FAQs
What is Low-Code and No-Code AI Platforms?
Low-Code and No-Code AI Platforms simplify AI integration for businesses without requiring extensive coding knowledge, enabling easier adoption and implementation.
What features should I look for when choosing a no-code/low-code development platform?
When selecting a no-code/low-code development platform, consider features such as ease of use, visual development competencies, integration abilities, scalability, app development support, available templates and pre-built components, collaboration features, security features, supplier support, and pricing fashions.
What is the future of no-code/low-code AI?
According to Gartner, by 2024, low-code and no-code app development will account for 65% of all app development. Organizations might also utilize no-code AI to install AI models that achieve unique business results and enhance operations while maximizing the value of their data.
Where can I discover more information about these no-code/low-code development platforms?
For more detailed information on these no-code/low-code development platforms, it’s highly encouraged to visit their websites. There, you can find comprehensive documentation, case studies, user reviews, product features, pricing details, and contact information for additional inquiries.
Are there community support resources available for those no-code/low-code development systems?
Yes, most of the no-code/low-code development platforms indexed have active community support sources. These encompass developer forums, information bases, documentation, consumer companies, and community-pushed events. It’s beneficial to explore these assets to leverage the collective expertise and help of fellow developers.
What is an example of low-code and no-code?
Here are some examples of low-code and no-code platforms: Low-code platforms: OutSystems, Mendix, Appian, and Microsoft PowerApps. No-code platforms: Airtable, Bubble, Zapier, Glide, and Webflow.