Cloud Based AI Services: An Informative Guide

Artificial Intelligence has received tremendous attention in the last couple of years. Using AI opens a new realm of possibilities for companies to explore more revenue streams, engage customers and strengthen brand position. However, the major roadblock comes with financial constraints imposed with the AI implementation of an enterprise.

When it comes to AI adoption, it becomes expensive for small and mid-sized enterprises to develop AI products in-house. Fortunately, large cloud service providers like Microsoft, Amazon, IBM, Google and others help to create an inexpensive and hassle-free AI implementation roadmap for SMEs. These cloud-based AI solutions benefit businesses with economic AI solutions, defined and pre-packaged services, lower risks, and access to modern technology.

Refer to the following Gartner stats to better know the applicability of cloud offerings for AI solutions.

  • By 2023, 40% of all enterprise workloads will be moved to cloud infrastructure and platform services, up from 20% in 2020.
  • By 2025, prime cloud service vendors will offer at least some distributed cloud services that execute to serve needs.
  • The global public cloud service market is expected to reach $623.3 billion by 2023.
  • By 2023, cloud-based AI will increase 5X ,making AI one of the preferred cloud services.

This informative guide lists the AI offerings of major cloud-based AI platforms and their applicability for business use cases. We will also offer our verdict on each of the cloud offerings.

Amazon Web Services

AWS pre-trained AI Services offer intelligence for business applications/workflows and cater to different use cases such as personalized recommendations, improving safety and security, modernizing contact centers, and fostering customer engagement. Amazon’s top-notch AI solutions include—

Amazon Forecast: Uses the same ML technology used by for forecasting future demand for products. With historical data and seasonal factors, Amazon Forecast solutions offer better insights on demand projections. 

Amazon SageMaker: Whether you need model preparation, building, training or deployment, AWS SageMaker offers a broad range of services designed specifically for machine learning.

Amazon Personalize: This AI solution empowers enterprises with real-time personalized recommendations. Amazon Personalize fortifies personalization experience with product recommendations, product re-thinking, and direct marketing. 

Amazon Fraud Detector: Amazon offers its fully managed service of online fraud detection to detect new account fraud, online payment fraud, loyalty program abuse, and guest checkout. This fraud detection AI service helps you secure your assets from fraudsters.

Amazon Rekognition: Amazon contributes to image and video analysis to detect scenes, objects, and faces. The Rekognition API offers a platform for visual search and discovery.  

Apart from the above specific use cases, Amazon also offers advanced Machine Learning solutions.

Amazon Machine Learning

Amazon facilitates ML model building for enterprises without having to learn complicated ML algorithms. You can harness Amazon’s ML offerings for every underlying ML task such as data extraction analysis, feature analysis, model monitoring, Continuous Integration and Continuous Development(CI/CD) of ML pipeline, etc.

For most of the Machine Learning tools, in-house expertise is obligatory. But Amazon ML also offers visualization tools and wizards that simplify your ML model development without having to learn complicated ML algorithms.

In addition to the above AI solutions, Amazon also aids with NLP, text analytics, chatbots, and document analysis solutions.

Retail, supply chain and manufacturing industries can benefit from Amazon’s pre-trained AI solutions to heighten customer experience, streamline demand planning and minimize risks.


With fully managed AI services, Amazon offers a seamless AI adoption experience with minimum resource requirements. However, implementation of ML models is not a simple affair, as it involves consideration of different aspects like data availability, AI infrastructure, and more. Fortunately, you can simplify your AI adoption journey by partnering with AI experts for a flawless experience.  

Microsoft Azure

Microsoft boosts your AI implementation experience with its rich offerings of AI Tools, AI solutions, and AI Infrastructure. Azure AI provide the following major solutions.

Anomaly Detector: Azure anomaly detector API enables anomaly detection with time-series data and the best fitting model to deliver high accuracy in detecting outliers. This solution will help you tackle unexpected drifts and keep accuracy intact.

Metrics Advisor: Microsoft brings intelligent monitoring to business metrics such as sales, revenues, and manufacturing operations. It helps explore organizational growth opportunities with apt anomaly detection, early warning mechanisms, granular analysis, and alerting.

Personalizer: Microsoft Azure nurtures rich and customized interactions by prioritizing content, conversations, and layouts. Personalizer can be used as either a standalone solution or in combination with other solutions.

Azure Bot services: Azure allows intelligent virtual assistant development to uplift customer experience. These bots deliver multichannel experience, a higher degree of sophistication, and natural language interaction.

Microsoft also offers cognitive search services like text analytics, translation, document analytics, custom vision, and Azure Machine Learning solutions. Azure AI framework includes Visual Studio tools for AI, Data Science VMs, Azure Notebooks, and Azure Machine Learning Studio. Microsoft Azure AI Infrastructure list is rich with Azure Data Services, Azure Kubernetes Services (AKS), GPUs- FPGAs and databases like SQL Server, PostgreSQL, MySQL, NoSQL, and MariaDB.

Azure provides AI offerings to various industries as mentioned below:

Manufacturing Industry 

  • Automated quality control
  • Proactive maintenance
  • Enhance staff safety

Finance Industry

  • Reduce crime
  • Boost customer experience
  • Modernize practices


  • Enable proactive care
  • Accelerate innovations
  • Improve practices and outcomes


Very similar to Amazon Web Services, Microsoft Azure ML capabilities are based on its real-time and live applications. Different businesses such as retail, logistics, inventory, financial services, manufacturing, healthcare can leverage their business practices by integrating Cloud Azure AI solutions.

Google Cloud

Similar to Microsoft and Amazon, Google leverages AI experience through its consumer-facing products. Following are some of the major offerings and applications of Google Cloud.

Contact Center AI: Google helps boost customer satisfaction and enhance contact center operational efficiency through Contact Center AI.

DialogFlow CX : It is used to create advanced chatbots that handle customer messaging, response, and voice recognition.

Digiflow: It is used to build virtual agents for mobile apps, messaging services, and IoT devices.  

Google’s Cloud Vision API: Recognizes objects, logos, and landmarks within content or images. Google leverages its matchless core search competency through this AI solution.

Natural Language API: Brings more clarity in content classification, entities, syntax, and sentiments. It also enables content conversion through Speech-to-text and text-to-speech APIs.

For expert ML developers, Google provides Machine Learning (ML) Engine with TensorFlow models that are trained for different scenarios. It offers an excellent prediction service using trained models. The beauty of Google AI Cloud Based Solutions comes with its TPU or Tensor Processing Unit, which is a special chip designed for TensorFlow. TPUs are 15-30x faster than CPUs and GPUs and offer 180 teraflops of computing power.  

Various industries such as education, publishing, retail, governance, NGOs, telecommunication, etc. can harness Google cloud capabilities for ML models, accurate predictions, and intelligent text processing.


Google’s Cloud based AI services facilitate better decision-making with end-to-end ML solutions. Google offers an all-inclusive ML development platform that enables effective decision-making backed by explainable AI, continuous evaluation, data labeling, pipelines, training, and what-if tool.

IBM Cloud

IBM has come out to be a powerful AI cloud partner after merging with SoftLayer data centers, BlueMix cloud service, and Watson AI group last year. IBM Cloud offers 170 services with more emphasis on data-speech conversions and analytics.  

  • IBM Watson Studio provides an excellent option to build and train AI models, prepare data, and perform analytics.
  • Watson Knowledge Catalog helps with intelligent data and analytics, governance, and cataloging.
  • Watson Discovery is useful to find relations and associations.

IBM strengthens data scientists and analysts with a Data Refinery App that enables deep learning using ML models such as neural networks and scales to huge data sets. IBM Watson Services for Core ML facilitates building AI-powered Apps that executes locally, offline, or in the cloud.

Various use cases of IBM cloud include—

AI for Financial Operations: Improved FinOps with planning, budgeting, and forecasting tools for explicable and informed decision making. AI-driven financial planning offers benefits such as better collaboration, agile operations, accelerated planning cycles, and scalability.

AI for security: Intelligent security framework powered by AI capabilities to detect, investigate and respond to threat events and secure enterprise from security hazards and attacks. IBM security solutions help in threat detection, cloud security, IoT security, data exfiltration, and compliance needs.

AI for supply chain: Effective supply chain planning with fewer disruptions, demand planning, and market shift considerations through accurate predictions. It ensures a smooth cycle of supply-demand with minimum wastage.

AI for IT Operations: Seamless ITOps through Watson AIOps. Quick troubleshooting and easy monitoring enable your IT teams to focus on core competencies and critical missions.

AI for healthcare: Data-driven approach transforming patient care experiences. Watson Health Solutions have diverse offerings from health economics and research to clinical decision support to disease research and treatment.


IBM is recognized as one of the leading partners for Cloud AI Services with its ML framework, APIs, and bots. IBM provides great value in terms of improvised processes and existing products. With focus on analytics, virtual assistants and natural language processing IBM would be the most comprehensive cloud AI partner.

Other Cloud AI Partners

While discussing cloud-based AI services, Oracle AI and Salesforce also deserve a special mention. However, they are comparatively unpopular for their lack of solutions and offerings.

Oracle AI: Oracle contributes with its cloud based AI services, such as data sources for data extracting and data mining. It also offers frameworks and tools for building ML applications.

Salesforce: Salesforce streamlines ML apps building and predictive analytics with its Einstein AI Platform that can be integrated with other Salesforce utilities. It supports building ML applications and predictive analytics on your Salesforce data. It also provides Sales prediction and chatbots, which are its typical offerings.

A Note on Attri Solutions

Enterprises face different roadblocks in their AI implementation. The major ones being lack of resources, infrastructure, data availability, timescale, and budget. Moreover, AI adoption requires collaborative teamwork between different stakeholders like software engineers, data scientists, analysts, ML engineers, and others. Most of the enterprises have limited skilled resources like ML engineers and data scientists.

Partnering with Attri for your AI implementation alleviates these roadblocks. We take care of your AI adoption needs by providing state-of-the-art solutions that best cater to your use cases while keeping AI adoption costs low and maximizing your returns with AI adoptions. 

Our unique offerings include -

AI Interoperability Platform

Using our flagship Interoperability Platform, enterprises can build AI solutions without locking in with any specific vendor. The platform integrates the best services and tools from different cloud providers under a single mesh.

Attri AI Solutions

We simplify your AI adoption journey with our tailor made solutions that are ready to deploy. Our solutions are thoroughly tested and are serving multiple industries for various applications. We help you leverage the power of cloud AI capabilities irrespective of your current cloud and AI infrastructure.

Attri AI Expertise

We uplift enterprise AI adoption experience with our AI expertise to accelerate AI deployment at any stage. Our experts help you tackle all the AI implementations roadblocks and guide you to build ML models that are efficient, reliable, and responsible.

With our expertise in the AI domain, we believe that the future of AI is an open ecosystem with interoperable AI platforms. Enterprise AI adoption should not be constrained by vendor lock-in, but enterprises should be able to boost up business with optimal revenue strategies and best-of-breed technologies. Consumption economics-driven AI adoption boosts enterprise-friendly AI adoption strategies with an open ecosystem, operator ease, and more value to enterprises.

We compiled this informative guide to educate you on cloud AI platforms. Drop an email at to share your feedback and queries.

Mugdha Somani

Mugdha Somani

As a former professor and publisher of technical books, Mugdha always keeps up with the latest academic and industry advances. An educator at heart, she enjoys sharing knowledge and connecting with likeminded folks.