Artificial Intelligence is helping businesses improve products and customer experiences, make data-driven decisions, and automate time-consuming tasks.
From chatbots and text analysis software to more complex predictive analytics tools, there’s a wide range of AI applications that businesses are looking to implement. But building an in-house AI solution doesn’t make sense for most businesses. It’s a long and complex process, which involves huge upfront costs.
That’s why businesses will often turn to AIaaS (AI as a service), third-party solutions that are ready to use right away.
Below, we’ll introduce the concept of AIaaS, the different types of solutions, and some of the top players in the market.
AIaaS is short for artificial intelligence as a service and refers to companies that provide out-of-the-box AI solutions.
By Artificial Intelligence, we mean computer systems that can carry out human-like tasks. This involves reasoning, learning from past experience, and solving problems. In other words, machines that can act and think like humans.
You may have also heard of software as a service (SaaS) or infrastructure as a service (IaaS). Just like AIaaS, they are ‘as a service’ solutions, hosted by a third-party provider, and a cost-effective alternative to developing software in-house.
AIaaS makes AI technology accessible to everyone. Through APIs and intuitive, low-code tools, users can harness the power of AI without writing a single line of code.
Plus, instead of months, it will take you just weeks to set up AIaaS solutions.
There are many different types of AI services, and when you’re ready to buy you’ll probably have a good idea of what you’re looking for – it will all come down to your pain points and what you need to improve. The three most popular types of AIaaS solutions are:
Chatbots use AI algorithms to simulate human conversation. They combine NLP and machine learning capabilities to understand user queries and provide relevant responses.
Bots are already revolutionizing customer care by reducing first-time response rates and improving customer satisfaction. They help businesses automate routine tasks, saving agents valuable time to focus on more complex tasks. They can also provide 24/7 assistance in real time and handle multiple queries without human help.
Many AIaaS solutions come with APIs. An API (Application Programming Interface) acts as an intermediary, allowing two pieces of software to interact.
Let’s say you want to automatically sort customer support tickets by topic as they drop into your helpdesk. Through an API, you can connect an AI tool like MonkeyLearn with your favorite customer service software.
You can use APIs for Natural Language Processing, sentiment analysis, and to extract entities from text, among other tasks. When offered ‘as a service’, APIs can be implemented right away and you’ll only need to write a few lines of code.
Companies use machine learning algorithms to find patterns in large amounts of data, make predictions, and streamline processes.
AIaaS makes it easy for businesses to adopt machine learning technology. You can use pre-trained models, or customize tools to suit specific business needs. All this, without needing any machine learning expertise.
When it comes to deciding on an AI service, it’s important to consider your goals, business size, and available budget. You’ll also need to assess the technical capabilities of your teams and the amount of data that you need to process. To help you make your decision, here’s a quick rundown of the top AIaaS companies:
Start your journey with a pre-trained model, like this survey analyzer to classify customer feedback by topic. Or build customized machine learning models to detect sentiment, keywords, and topics in your data. Then, integrate models to your favorite apps through point-and-click integrations or via the API.
Finally, run your models in MonkeyLearn Studio to create powerful dashboards and gain actionable insights.
Check out MonkeyLearn’s plans and pricing.
IBM Watson hosts a suite of AI tools to help large companies make the most of their data.
There are many pre-built applications, like Watson Assistant (to build virtual assistants) and Watson Natural Language Understand (to perform advanced text analysis tasks).
Developers can use IBM Watson Studio to build, train, and deploy machine learning models across any cloud. No expertise on machine learning or data science is required.
To find the service that best adapts to your use case, sift through their portfolio of solutions
With Azure Cognitive Services, you can add different AI capabilities (like computer vision or text extraction) to your apps using APIs. You might also want to use Azure Bot Service, allowing you to intuitively build any type of bot, from a Q&A bot to your own branded virtual assistant.
With AutoML, you can train custom machine learning models for text analysis, image classification, translation, and more. You can visualize your datasets to see how your model works using a “what-if tool” and get metrics to assess performance.
One of the advantages of using this platform is that you can easily integrate your models with all the Google Cloud ecosystem.
Artificial Intelligence as a Service (AIaaS) makes AI technology accessible. It provides fast, cost-effective, and ready-to-use solutions with minimal effort.
In most cases, developing AI software in-house is not an option. With an AIaaS you can pay for the tools you need and upgrade to a higher plan as your business and data scales.
November 20th, 2020