With artificial intelligence (AI) gaining popularity every day, it’s no wonder so many companies want to use AI-powered tools to their advantage. The only problem is, which tool is right for their needs? 

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In today’s digital era, 73% of US companies use AI in some aspect of their business, whether for brainstorming ideas, writing code, or generating text and images. 

But with so many good tools that do literally everything, it’s hard to figure out which AI-powered tool to start with. Do you want predictive analytics or a tool that streamlines the design lifecycle? 

Either way, you need a guide to start with. Luckily, you’ve stumbled upon the best resource for this topic, as we’ll explore the benefits of an AI platform, how to choose the right one, and the top 12 tools for your business. 

What is an Artificial Intelligence Platform?

An AI platform is software that performs different tasks usually performed by humans, such as learning, reasoning, problem-solving, etc. These platforms use AI, machine learning (ML), and natural language processing to develop, deploy, and manage AI apps. 

Basically, AI platforms help developers and businesses build AI-powered solutions more efficiently, with less expense and fewer resources. 

In general, they have data processing capability, facilitate training for the models, and offer tools for visualizing data and performance.

So, now you know what’s what. Let’s go straight into the crux of the problem and see the top 12 AI platforms. 

What are Some Top AI Platforms?

So, you’re curious about the best AI platforms for businesses. We were also curious about them; that’s why we’ve spent hours searching for the best AI tools that will streamline your business workflows.

Here they are: 

1. Guru – Best AI-driven platform for streamlining your knowledge base. 
2. Rasa – Best AI-powered platform for building conversational AI chatbots and assistants. 
3. Vertex AI – Best beginner-friendly platform for building virtual assistants and applications. 
4. Microsoft Azure – Best platform for building generative AI models and apps. 
5. OpenAI ChatGPT – Best chatbot and AI assistant that mimics human conversation on any topic. 
6. H2O.ai – Best AI-driven solution for gathering valuable information from datasets and documents. 
7. TensorFlow – Best open-source library for building and deploying ML models. 
8. IBM Watson – Best platform for building, training, validating, and deploying AI models. 
9. Amazon SageMaker – Best AI platform for building and deploying ML models. 
10. PyTorch – Best deep learning software for building AI applications. 
11. Claude.ai – Best next-gen AI assistant for automating various tasks. 
12. Dataiku – Best AI-powered platform for deploying and managing data and analytics. 

These platforms all sound nice in theory, but do they live up to their name? The answer is yes, they do. Find out for yourself by reading on... 

1. Guru

Guru is more than just a simple tool. It’s an enterprise AI, wiki, and intranet — all in a single platform. 

What Guru does is take your company’s collective knowledge and use AI to push relevant (and timely!) information to those who need it most. Without switching apps, mind you.

So, you get a centralized source of truth for all your company knowledge as Guru captures information from all your chats, docs, and apps. Whenever someone raises an inquiry, they can get the answers quickly. 

Besides, Guru integrates with OpenAI’s ChatGPT to help people get answers and find inspiration without leaving ChatGPT. This powerful combination of tools allows you to access your company’s knowledge more easily. 

“I use it every day. It’s very user-friendly. It works just like Google, all you need [...] is [...] a keyword and bang — you’ll find what you’re looking for.” 

Want to learn more about Guru? Watch our on-demand demo video now! 

Top features

• AI-powered content suggestions: Guru’s AI will offer employees useful answers based on what they’re working on.
• Customization options: Make Guru feel like your personal home base by customizing it with your logo, brand colors, etc. 
• Templates: If you’re out of ideas or don’t know where to start, Guru has pre-built templates that make it easier for you to create content.

Use cases

Guru is the perfect solution for companies of all sizes that want to streamline their knowledge. 

2. Rasa

Rasa is an AI-powered solution that lets companies of all sizes build AI chatbots and assistants that offer conversational experiences and automated interactions to customers. 

It’s a good tool for improving your customer service because it lets you build AI assistants through a mix of a no-code user interface and a conversational AI engine. 

As a result, Rasa enables more nuanced and meaningful interactions and conversations with your customers, and can respond to inquiries via natural language processing (NLP) capabilities. 

But it’s also built with state-of-the-art security measures, so enterprises can rest assured that it won’t use personal data without their permission. 

“Rasa is an open-source framework for building conversational AI. It is more customizable for different use cases and business problems.” 

Top features

• Drag-and-drop interface: Rasa’s user interface is easy to use and is very effective for cross-team collaboration. 
• Deployment modes: You can choose to deploy the chatbot on-site or in a private cloud, giving you the flexibility to control your data. 
• Multi-channel customer experience: With Rasa, you can engage your customers in 10 built-in messaging channels, all powered by a backend assistant. 

Use cases

Rasa is ideal for industries such as financial services, healthcare, telecom, travel, and transport due to its advanced features. 

3. Vertex AI

Vertex AI is Google’s centralized platform powered by AI, a tool that offers all of Google’s functionalities in a single place. 

It has a single purpose: to train machine learning and AI models and make it easier to deploy them at scale. What this means is that you automate the model development process and build helpful chatbots faster. 

But you can also customize large language models (LLMs) to use in various AI apps, significantly boosting your productivity. 

Moreover, it’s a great solution for maintaining consistency and creating AI models of the same quality and with minimized errors. 

“Vertex AI makes it easy to prepare data, train models, and deploy them. The tools and services work well together, which saves time and effort.” 

Top features

• AutoML: This feature helps beginners build their own custom ML model easily and works for various Google applications. 
• Model versioning: With Vertex AI, it’s super easy to keep track of your model’s versions and monitor its performance. 
• Pre-trained APIs: Even if your developers have no prior experience, it’s easy to integrate videos, translation, and NLP into the models with this tool. 

Use cases

Vertex AI is a good solution for ML engineers and developers since it’s so beginner-friendly. 

4. Microsoft Azure

Microsoft Azure offers a platform that deploys generative AI solutions. It uses the latest open and multimodal models for fast innovation and lets you build the perfect tool for your use case. 

To create the AI apps they want, developers can use their favorite tools and language to code the model, as well as an open-source framework that makes it easier to deploy them. 

That’s not all — you can also accelerate machine learning projects through capabilities like model development and training and data preparation. 

“I feel Microsoft Azure is an easy-to-use cloud platform for all of the company's needs in the information technologies, from renting a virtual machine to AI-powered application deployment.” 

Top features

• AI search: Using a combination of advanced retrieval augmented generation (RAG) and modern search, Azure can deliver intuitive responses every time. 
• Phi-3 open models: Azure uses small language models (SMLs) that maximize AI’s capabilities with lower resource use and latency. 
• ML prompt flow: Using agile prompt flows, you can simplify the way you use AI solutions throughout the entire ecosystem. 

Use cases

Microsoft Azure is a solution built for the IT industry. 

5. OpenAI ChatGPT

ChatGPT — as you well know by now — is a popular chatbot and virtual assistant created by OpenAI. Using LLMs, ChatGPT can mimic human conversations and respond to questions easily. 

With ChatGPT, you can ask questions or ask it to generate images or text via prompts. Simply write the request and ChatGPT will do its best to generate an answer in real time. This makes ChatGPT an ideal solution for researching topics, learning new skills, or creating content. 

ChatGPT is so intelligent that it can follow up on questions, admit its mistakes (if it makes any), and reject inappropriate requests. In short, it’s like chatting with a friend rather than a computer. 

“ChatGPT is a wonderful tool that helps in our daily tasks, from generating captions and text copies to solving Excel tasks. This is incredible if you know how to give the right prompts!” 

Top features

• Image generator: Aside from crafting text, ChatGPT also helps with generating high-quality images and art, based on text prompts. 
• Voice and audio recognition: You don’t need written text to ask ChatGPT anything. This helpful chatbot recognizes accents and different languages and can respond to prompts easily. 
• Code writing: ChatGPT is the perfect companion for developers who want to write code or learn different languages. 

Use cases

You can use ChatGPT for anything, as it has general knowledge about every topic. It’s great for personal and professional use. 

6. H2O.ai

H2O.ai is a cloud-based AI solution that has one goal: to increase business productivity. How? By drawing valuable and actionable insights from data (both structured and unstructured) to try solving complex problems. 

Moreover, it’s a trusted AI provider that helps enterprises of all sizes be more strategic and accelerate innovation. H2O offers multiple functionalities, such as open-source distributed machine learning, automatic machine learning, and a solution for business users. 

Through predictive and generative AI, H2O focuses on supercharging your productivity by processing hundreds of documents in different ways, such as translating, summarizing, or inspecting them. 

“Easy to use with good UI design and automated ML function. Driverless AI has strong capability [in] auto feature engineering and system visualization.” 

Top features

• Driverless AI: This feature works by delivering autoML capabilities created specifically for making AI, using automation combined with data science. 
• Hydrogen Torch: H2O offers a no-code deep learning toolkit that helps you train AI models faster and better. 
• Document AI: Through artificial intelligence, H2O can extract valuable information from your documents easily. 

Use cases

H2O is an open-source platform suitable for data scientists and companies in multiple industries. 

7. TensorFlow

TensorFlow provides an open-source library that businesses can use to build ML algorithms that run in every environment. 

TensorFlow offers assistance in all the stages of the development process, from processing data to deployment to debugging. Developers can build ML apps in different programming languages, such as Python, Java, C++, etc. 

In a nutshell, TensorFlow makes it easy to build machine learning platforms at scale. 

“The way it handles the data and the community support, it has [been] a [godsend]. Developing and maintaining the code base is really easy with TensorFlow.” 

Top features

• Flexibility: TensorFlow is a flexible tool that allows you to make modular or standalone ML models. 
• Parallel neural network training: TensorFlow can help you train multiple neural networks and GPUs and streamline your pipeline. 
• Open source: TensorFlow is free to use for everyone, allowing you to build and deploy the best machine learning model. 

Use cases

TensorFlow is for businesses, developers, and researchers that want to build high-quality ML models. 

8. IBM Watson

IBM offers a state-of-the-art studio where people can build, train, and deploy AI models. It’s called watsonx.ai and it combines generative AI capabilities with foundation models and traditional machine learning to streamline your processes. 

It’s much easier to build AI apps this way than doing it on your own. With watsonx.ai, it takes less time and less data due to its easy-to-use tools and more refined prompts. 

You can choose from different models (which means the tool is flexible) like the Granite, open-source, or third-party models. But you can also bring your own custom model. 

“The ease of use and access, plugging an LLM [into] a website to scrape pages and produce output in a jiffy. The integration is easier, you can plug [into] any existing applications and launch a chatbot on your website.” 

Top features

• Flows engine: watsonx.ai simplifies the generative AI development process through intuitive flow language, which makes apps easier to deploy to the cloud. 
• Tuning studio: IBM offers a tuning studio where you can optimize and prompt-tune your models for better performance and accuracy. 
• Prompt lab: Users can use the Chat, Freeform, and Structured modes to tinker with their prompts and craft the best model. 

Use cases

IBM watsonx.ai is for businesses of all sizes and industries. 

9. Amazon SageMaker

Amazon SageMaker is a platform where data scientists and developers can build, train, and deploy machine learning models at scale. 

Since it’s a fully managed service tool, SageMaker offers a range of tools (such as debugging, pipelines, MLOps, etc.) that make it easier, effective, and low-cost to build high-performance ML models for any use case. 

Anything you need, SageMaker can provide. It’s a solution that also excels at building financial management systems (FMs) by using LLMs trained on massive datasets. 

“SageMaker makes it very easy to train and deploy models. The managed infrastructure allows us to focus on business logic without needing to deal with things like cluster management, autoscaling, etc.” 

Top features

• Canvas: This functionality allows you to build accurate ML models via a very intuitive and visually appealing interface. You don’t need coding experience to use it. 
• Data wrangler: With SageMaker, it’s easier to aggregate and prepare image or tabular data in minutes rather than months. 
• Notebooks: You can build machine learning models with notebooks, code, and data in the integrated development environment (IDE).

Use cases

Amazon SageMaker is for teams of all sizes in different industries, including cybersecurity, financial services, etc. 

10. PyTorch

PyTorch, developed by a research lab, is deep learning software offering multiple frameworks for building AI applications. 

What PyTorch provides is a user-friendly interface that makes it easy to build deep learning models easily in different programming languages. 

This open-source framework is ideal for beginners who want to dabble in this industry and build intelligent AI applications. 

“One of the things I really appreciate about PyTorch is how user-friendly it is. It makes the complex realm of learning more accessible, which is fantastic. [...] It feels effortless to implement ideas thanks to its integration with Python [...]” 

Top features

• Distributed training: Through torch.distributed backend, you can work on performance optimization and scalable distributed training in research. 
• Robust ecosystem: PyTorch has thousands of tools and libraries that support the development of NLP, computer vision, etc. 
• Cloud support: All major cloud platforms support PyTorch, so you can rest assured that it’s easily deployed on these channels. 

Use cases

PyTorch is a great tool for businesses in industries such as healthcare, retail, education, manufacturing, etc., that want to use AI technology.

11. Claude.ai

Claude.ai by Anthropic is a next-gen AI assistant similar to ChatGPT in the sense that you can ask it to do anything, whether that’s brainstorming ideas or providing data analytics. 

Powered by constitutional AI, Claude puts a heavy emphasis on security and data privacy. 

Moreover, Claude can process large amounts of data, generate text, and help you understand difficult subjects. You can even tailor it to fit your needs, use cases, and requirements. This allows you to focus on what matters most instead of wasting time. 

“What’s most useful about Claude is the AI’s ability to flow more naturally. I like that responses feel more like human-to-human conversation.” 

Top features

• Task automation: Claude assists with a wide range of tasks, such as writing code, drafting emails, etc. 
• Data analysis: Claude helps you get valuable insights out of your data and even interprets the result. 
• Language translation: Claude is capable of translating multiple languages. 

Use cases

Claude is useful for companies of all sizes. 

12. Dataiku

Our list ends with Dataiku, your everyday AI platform for building, managing, and deploying data and analytics. 

With Dataiku, you can build data into your daily operations, from generative AI apps to AutoML to MLOps. From one centralized end-to-end place, you can build projects faster, in days instead of weeks, and foster collaboration among team members. 

“The ability to automate tasks like model deployment and report generation is a game changer. Dataiku frees up data scientists to focus on higher-level analysis and innovation [...]” 

Top features

• Data preparation: Dataiku allows coders and non-coders to access and explore project data in a shared space. 
• Generative AI: With Dataiku, you can build generative AI applications at scale. 
• Visualization: Dataiku’s built-in functionalities are perfect for data profiling, charting, and more, using tools like pie charts, heat maps, tables, etc. 

Use cases

DataIku is for diverse companies and different use cases. 

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So many good tools, so little time to get to know them all. If one piqued your interest, then go ahead and research it further.

If you’re not convinced yet, let’s go through the benefits of using AI platforms. 

What are the Benefits of Using AI Platforms?

AI platforms have plenty of benefits, one of them being an increase in revenue. On average, companies can expect a 6% to 10% revenue growth from the adoption of AI, so it’s highly profitable to invest in AI-powered tools now.

But there are other advantages, such as: 

• Automating repetitive tasks: The biggest benefit of AI platforms is their ability to automate mundane tasks and free human workers to focus on more strategic activities. By improving workflows and operations, you’ll enable increased productivity and even speed up task completion time. 
• Minimizing errors: We all make mistakes, we’re human after all. But some mistakes are too costly to ignore. AI platforms reduce the chance of manual errors and are less likely to make mistakes when it comes to data entry.   
• Enhancing customer experience: There are many AI virtual assistants out there that help streamline the customer experience by answering questions and being there for customers when they need it most. Moreover, chatbots are great for generating highly personalized messages that help customers find the best solution for their issues. 
• Enabling better decision-making: AI platforms do one thing well and that is to analyze data and trends and come up with innovation opportunities. With this unbiased data analysis, you can make better decisions regarding your business and its operations. 

Sure, AI algorithms do have their benefits, even increasing leads and appointments by as much as 50%. 

But they also have their share of challenges. Let’s take a look at them. 

What are the Potential Challenges of AI Platforms?

As much as we want it to be, AI is far from perfect. Whenever you invest in AI services, you have to get ready for the following challenges: 

• Cost: Building an AI platform requires time and resources. If you want it to be complex, with multiple functionalities, then the costs for its development might run a bit high. Plus, it needs to be updated, so it must use the latest technology to operate. 
• Security risks and privacy concerns: Many people are concerned about how AI solutions use their personal data, especially if used without consent. Besides, AI is vulnerable to cyberattacks, as it can be manipulated to cause potential harm. 
• Data dependence: AI thrives on data. Without data, AI platforms can’t perform the tasks they’ve been assigned to. AI requires high-quality data — a good amount, too — to stay up-to-date and perform effectively. 
• Bias and fairness: Depending on the data you feed it, AI can come up with risky and discriminatory content that might harm your reputation if unchecked.

It doesn’t sound that bad. The benefits outweigh the cons, so you should still consider investing in AI platforms if you want to. 

Next, let’s see how to choose the best AI platform for your business. 

How to Choose the Best AI Platform for Business

There are three selection criteria when it comes to choosing the AI platform of your dreams: 

• Key features: There are so many features the AI platform should have, it’s gonna take a while to mention them all. Consider platforms with AutoML (so it automatically chooses the best algorithm), collaboration tools (multiple users can work together), and continuous improvement to keep data fresh. Another thing to keep in mind is integrations, if the new AI tool is to fit perfectly with your existing tools. 
• Core functionalities: AI platforms should be able to clean and process data to be usable. But they should also train models using various algorithms, evaluate the reliability of the ML or AI models, and deploy them. 
• Usability: Make sure the AI solution is easy to use and has an intuitive interface, so even beginners can build apps really quickly. Also, look for tools that have drag-and-drop features and learning resources in case you’re stuck on something. Responsive customer support is also a must-have. 

Seems like we’ve included all there is to know about AI platforms. Hopefully, it has guided you in the right direction and convinced you to make the right decision. 

But there’s only one true decision…

Over To You!

…and that is Guru! 

Guru is the perfect AI-powered solution that helps you manage your internal and external knowledge and create helpful wikis. With this tool, you can take your company’s knowledge to new levels and get relevant info whenever you need it most. 

So, ready to have data at your fingertips? Sign up for Guru today to see how it feels.

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