Top 11 AI as a Service Companies 2023

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Artificial Intelligence as a Service (AIaaS) companies use a combination of AI and the “as a service” model. It is a cloud-based service model offering AI outsourcing by providing AI capabilities and infrastructure to organizations without requiring them to develop or maintain their own AI systems.

AIaaS companies are driven by a key mega-trend: Artificial intelligence (AI) is becoming commonplace in enterprises across industry sectors. Almost all businesses use at least one AI or cloud-based service to gain a competitive edge and outsource their needs to third-party vendors. Consequently, AIaaS companies are forecast to grow dramatically in the years ahead.

Jump to:

• • AI as a Service Companies: Comparison chart
  • IBM Watson: Best for automating complex processes
  • AWS AI Services: Best for features and global presence
  • Microsoft Azure AI: Best for developers and data scientists
  • Google Cloud AI: Best for data analytics
  • ServiceNow: Best for workflow automation
  • Salesforce Einstein AI: Best for marketing teams
  • Alibaba Cloud: Best for affordability
  • MonkeyLearn: Best for text analysis
  • DataRobot: Best for building custom models
  • Oracle Cloud Infrastructure (OCI): Best for anomaly detection
  • The Future of AIaaS
  • How to Choose the Best AI as a Service Company
  • Bottom Line: AI as a Service Companies

AI as a Service Companies: Comparison Chart

Best AI as a Service Companies

IBM Watson: Best for Automating Complex Processes

In the field of artificial intelligence, IBM has developed and offers a cognitive computing platform called IBM Watson. Watson is an AI system that combines natural language processing, machine learning, and other advanced technologies to analyze and understand large amounts of data. It has been used in various industries, including healthcare, finance, retail, and customer service, to provide insights, make recommendations, and assist with decision-making.

You can select from a variety of prebuilt apps from IBM Watson, including Watson Orchestrate for automating complex processes, Watson Assistant for building virtual agents, Watson Code Assistant, which helps developers write code with AI-generated recommendations, and Watson Discovery for content analysis.

Key features

• Natural language processing (NLP).
• Developer Tools and APIs.
• Data virtualization.
• Model development.
• Text, image and video analysis.

Pros

• Discovery and insights.
• It can help you generate code with applicable syntax from a natural language request.
• Speedy data discovery capability.

Cons

• Users reported that the tool has a steep learning curve.
• It may be too expensive for small businesses.

Pricing

IBM charges different rates for its various products and services. The amount you will pay depends on your chosen product. For instance, the IBM Watson Orchestrate base edition costs $200 per seat per month, Watson Assistant Plus plan starts at $140 per month. Watson Discovery Plus plan starts at $500, while its Enterprise plan starts at $5,000. Contact the IBM sales team to get the actual rate for your selected AI service.

AWS AI Services: Best for Features and Global Presence

Amazon Web Services (AWS) is a leading provider of cloud computing and AI services. The company offers various AI and ML services that can be segmented into different categories, including computer vision services like Amazon Rekognition, an image and video analysis tool, and Amazon Lookout for Vision for detecting defects and automating inspection. AWS also offers language AI tools such as Amazon Lex, a tool for building chatbots and virtual agents, and Amazon Transcribe for automatic speech recognition.

AWS offers hundreds of services worldwide, with data centers in multiple regions. This makes it an ideal choice for companies seeking an AI service provider with a global presence.

Key features

• AWS marketplace – an online store where a customer can search for software to buy for their business.
• Amazon Fraud Detector for online fraud detection.
• Amazon Forecast for forecasting business metrics.
• Code and DevOps services to improve application availability, perform automated code reviews and eliminate costly, inefficient code.

Pros

• Global presence and cost-effectiveness.
• Highly performant.
• Unlimited server capacity.

Cons

• Confusing billing due to price variations.
• Charges technical support fees.

Pricing

The amount you pay AWS depends on your selected service. You can also use the AWS calculator to get an estimate. Select the service you want to buy and follow the prompt on the screen to get an estimate.

Also see: Top Generative AI Apps and Tools

Microsoft Azure AI: Best for Developers and Data Scientists

Azure AI is a portfolio of AI services built for data scientists, developers, engineers and machine learning experts. With its knowledge mining platform, you can use Azure cognitive search to get insights from various types of content, including documents, images and media. Businesses looking to make their customer service more efficient and free up agents’ time to focus more on complex support tasks may find Azure conversational AI beneficial, as the Azure bot services let you build a multilingual and multimodal bot for your enterprise use case.

Key features

• Its machine translation capability lets you translate text and documents in real time in over 100 languages and dialects.
• Document process automation.
• Natural language processing.
• Built-in governance, security, and compliance.

Pros

• High availability.
• Users praise its role base access control capability.

Cons

• Requires platform expertise.
• Users reported that the Azure solutions are pricey.

Pricing

Microsoft Azure pricing varies based on your selected service. For instance, Azure Bot Services Premium Channels give you up to 10,000 messages per month and charge $0.50 per 1,000 messages. Azure Cognitive Search Basic plan costs $0.11 per hour, while its Storage Optimized L2 costs about $7.68 per hour. Its Open AI pricing also varies based on your model. To get the actual rate for your use cases, check the pricing page of your chosen Azure AI service or contact a sales representative for detailed quotes.

Google Cloud AI: Best for Data Analytics

Google, a leader in AI and data analytics, has been at the forefront of AI research and development, and its AI efforts encompass a wide range of applications, tools, and services.

Google has made significant contributions to the field of machine learning and deep learning. Its framework, TensorFlow, is an open-source library widely used for building and deploying machine learning models. Google also provides a suite of AI services through its Google Cloud Platform (GCP). This includes pre-trained models, APIs, and tools for natural language processing, computer vision, speech recognition, translation, recommendation systems, and more. Developers can leverage these services to integrate AI capabilities into their applications and workflows.

Key features

• Its generative AI tool, Google Bard, can help users create content.
• Its Studio Bot, which is an AI-powered coding assistant, can help Android developers fix bugs.
• Google’s PaLM 2 model can be used to build generative AI applications.
• The Cloud Vision API can identify objects, detect faces, read expressions and find similar images on the Web.

Pros

• Straightforward initial setup.
• Easy to train models.
• Integration with Google ecosystem.

Cons

• Limited customization.
• Customer support can be improved.

Pricing

Contact Google’s sales team for the price of your desired services. You can also check Google’s Vertex AI pricing page for the consolidated prices of their AI services.

Also see: Generative AI Companies: Top 12 Leaders

ServiceNow: Best for Workflow Automation

ServiceNow is known for its focus on automating workflows and improving service delivery across various departments within an organization. ServiceNow AIOps is a capability within the ServiceNow platform that combines artificial intelligence, machine learning, and automation to enhance IT operations management and drive proactive problem resolution.

Key features

• Search and automation, which includes AI search and automation discovery.
• Natural language processing capabilities which include foundational NLP, natural language understanding, NLU workbench and natural language query.
• Machine learning frameworks like similarity, classification, clustering and regression.
• Root cause analysis.

Pros

• Automation and remediation.
• Improve DevOps.
• Enhance the organization’s configuration management database (CMDB).

Cons

• The reporting feature can be improved.
• Steep learning curve for new users.

Pricing

ServiceNow encourages buyers to book a demo to learn more about the platform and also learn about the customer’s needs. Your requirements will be used to create your rates.

Salesforce Einstein AI: Best for Marketing Teams

Einstein is a Salesforce AI platform. It is integrated into various Salesforce products and offers a range of AI-driven features and capabilities to enhance sales, marketing, service, and overall customer engagement. The platform enables businesses to build AI-powered apps, automate processes, and gather insights to transform customer experiences. Einstein AI can perform complex tasks such as natural language processing, predictive analytics and machine learning to automate operations and uncover insights into customer data and behavior.

Key features

• Einstein’s vision lets you see the conversation about your brand on social media.
• Recognize text in images.
• It lets you build natural language processing into your apps to classify the underlying intent and sentiment.
• The platform allows users to build, train, and deploy custom bots on digital channels connected to their CRM data.

Pros

• Automatic speech recognition.
• Social image recognition.
• Lead scoring.

Cons

• Limited end-user customization.
• Some users reported that the Tableau CRM lacks some functionalities and can be improved.

Pricing

Sales Cloud Pricing:

• Starter: $25 per user per month, billed annually.
• Professional: $75 per user per month, billed annually.
• Enterprise: $150 per user per month, billed annually.
• Unlimited: $300 per user per month, billed annually.

You can add Einstein AI and Analytics to Service Cloud at $50 per user per month, billed annually.

Alibaba Cloud: Best for Affordability

With their expertise in big data analytics, natural language processing, image recognition, machine learning algorithms, and more, Alibaba’s AI and Data Intelligence platform is enabling companies to build intelligent applications that drive business value. The company provides numerous services, including virtual cloud servers, databases, storage systems, security solutions, big data services, and analytics tools.

Key features

• Vision AI includes optical character recognition, image recognition and videos.
• Intelligent Speech includes intelligent speech interaction, speech synthesis and speech analysis.
• Natural language processing includes machine translation and content moderation.
• It offers conversational AI capabilities and allows users to build multilingual chatbots over multiple channels to respond quickly to customers 24/7.

Pros

• Real-time speech transcription.
• Data intelligence application and visualization.
• Reliable documentation and support.
• Affordable pricing compared to some of its competitors.

Cons

• Limited presence outside Asia.
• Less familiar to engineers.

Pricing

Alibaba doesn’t advertise rates on its website. Interested buyers must contact the company for custom quotes.

Also see: Generative AI Examples

MonkeyLearn: Best for Text Analysis

MonkeyLearn is one of the best text analysis tools. With MonkeyLearn, users can access a repository of pre-trained models or train their own models to handle different tasks such as sentiment analysis, topic classification, keyword extraction, and content categorization.

With customer sentiment analysis, users can know their customers’ opinions about their products and services. This insight can be used to improve their customer experience. MonkeyLearn also makes it easy to analyze large amounts of unstructured data, such as social media posts and customer reviews.

Key features

• Data visualizations.
• Pre-built and custom machine learning models.
• Supports NPS, CSAT, survey, VoC, review, and support analysis.
• Text extraction includes feature extraction, keyword extraction, and entity extraction.
• Integrates with third-party services like Zendesk, Freshdesk, Medallia, Typeform, Airtable and more.

Pros

• Highly-customizable.
• Intent detection capability.
• Offers low-code, no-code text analytics.

Cons

• Expensive for small businesses and startups.
• Limited integration with third-party services.

Pricing

MonkeyLearn offers two pricing and plans.

• Team: $299 per month for up to three seats, three models and workflows, and 10K queries per month.
• Business: Custom pricing.

DataRobot: Best for Building Custom Models

DataRobot is an enterprise AI provider that helps companies build and deploy AI and machine learning models. It uses automated machine learning techniques to streamline the model development process. DataRobot automates various steps such as data preprocessing, feature engineering, model selection, and hyperparameter optimization.

Key features

• Production model lifecycle management.
• Prepare modeling data.
• Connects with data platforms like Google Big Query, Databricks, Amazon S3, Snowflake and more.

Pros

• Service health monitoring.
• Process large amounts of data quickly.
• Extensive feature engineering capability.

Cons

• Pricing is on the high side.
• The user interface can be improved.

Pricing

Although DataRobot doesn’t advertise its pricing on its website. Public available data shows that DataRobot AI Cloud, Starter Pack for AutoML, AutoTS, and MLOps costs $98,000 for 12 months.

H2O.ai: Best for Analytics and Predictions

H2O.ai is a platform of artificial intelligence and machine learning technologies powered by AutoML and no-code deep learning engines. It provides open source software, support, and services for developing machine learning models. H2O.ai specializes in developing predictive analytics and deep learning models that automate business processes and provide actionable insights. It offers a suite of products and services, including H2O Driverless AI, H2O AI Cloud, H2O Sparkling Water, H2O document AI, H2O-3, H2O Feature Store, and H2O Wave.

H2O.ai featured use cases include claims management, hospital capacity simulator, fraud detection and prediction of out-of-stock risks.

Key features

• Distributed, in-memory processing.
• Machine learning interpretability.
• It can automatically visualize and address data quality issues.
• Automates data science and machine learning workflows such as model tuning, model deployment, feature engineering, model validation, and model selection.

Pros

• The user interface is user-friendly and easy to use.
• A large community of users and developers supports it.
• H2O.ai’s models are able to handle complex data structures and large data sets.

Cons

• Documentation can be improved.
• It can be expensive and out of reach for small businesses or individuals.

Pricing

H2O.ai doesn’t advertise rates on their websites, they encourage buyers to contact their sales team for quotes. Publicly available data shows that H2O.ai Cloud costs $50,000 per unit – at least four AI units. They charge $200,000 for 12 months, $400,000 for 24 months and $600,000 for 36 months. H2O.ai Driverless AI Latest (BYOL) estimated infrastructure costs $3.06 per hour.

Oracle Cloud Infrastructure (OCI): Best for Anomaly Detection

Oracle provides multiple AI services, including digital assistant, which enables organizations to build conversational agents for business applications through text, chat, and voice interfaces. Speech-to-text services that help customers convert audio to text. Their AI Vision service allows customers to add image recognition capabilities.

Additionally, the company offers document analysis, AI forecasting, and anomaly detection. Customers can use these services to derive insights, glean new understanding from data, and automate processes.

Key features

• Prebuilt, conversational chatbots.
• Anomaly detection for managing assets and predictive maintenance.
• Text analysis capability.
• Real-time speech recognition.

Pros

• Sentiment analysis capability.
• High availability and fault tolerance.

Cons

• High-end cost.
• Technical support response time can be improved.

Pricing

Oracle pricing varies based on your selected service. For instance, Oracle Digital Assistant Cloud Service costs $0.0232 per unit, text translation costs $10 per unit, and pre-trained inferencing for over 5,000 transactions costs $0.25 per unit, and so on. Your actual price depends on your selected service, transaction volume and other factors unique to you.

Also see: 100+ Top AI Companies 2023

The Future of AIaaS

With several key trends and developments, the future of AIaaS is promising. Here are some potential directions for the future of AIaaS:

• Increased adoption: As AI technologies continue to mature and demonstrate their value across various industries, the adoption of AIaaS is likely to increase in areas like healthcare, finance, retail, and manufacturing.
• Advanced AI models: AIaaS providers will continue to develop and deploy more advanced and specialized AI models to tackle complex problems.
• Edge AI and IoT Integration: With the proliferation of the Internet of Things (IoT) devices, AIaaS will integrate with edge computing capabilities to bring AI processing and inference closer to the data source, reducing latency, improving response time, and enhancing privacy and security.
• Democratization of AI: As AIaaS becomes more accessible and user-friendly, it will empower non-experts to leverage AI technologies effectively. This democratization will enable a broader range of users and businesses to harness AI for various applications.

How to Choose the Best AI as a Service Company

Choosing the best AIaaS company requires careful consideration. Before selecting a company, assess the breadth and depth of AI services offered by the company. Consider whether their offerings align with your specific needs. As a general rule of thumb, it is best to consider a provider that offers a wide range of AI capabilities, such as natural language processing, computer vision, machine learning, or deep learning, depending on your requirements.

Evaluate the pricing model and cost structure of the AIaaS provider. Consider factors such as subscription fees, usage-based pricing, or any additional costs for customization, training, or ongoing support. Also, be sure to research the reputation of the AIaaS company by exploring reviews, testimonials, and industry feedback.

Bottom Line: AI as a Service Companies

AI as a service companies offer businesses access to cloud-based artificial intelligence technologies, a feat that is otherwise nearly impossible for most companies to achieve on their own due to limited or lack of resources, limited experts or internal skill sets. AIaaS companies are democratizing access to artificial intelligence and helping businesses discover new insights, track trends, automate digital processes, and study customer behavior quickly in near-real time, all without worrying about infrastructure or hardware investments.

The 11 AIaaS companies reviewed in this guide rank the highest in the AI sector and offer their customers the best-of-breed AIaaS solutions driving the highest customer satisfaction. These companies are helping to advance the industry’s technology and lowering the entry barriers to AI for a wide swath of businesses.