AWS AI ML Stack artificial-intelligence solutions in the AWS

Architect artificial intelligence (AI) solutions in the AWS

Architect AI solutions in the AWS using Amazon Sagemaker, Comprehend, Rekognition, Texteract & other artificial intelligence MLaaS offerings

AI is becoming sentient. As if we were not already mesmerized by AI capabilities i.e., from personalized product recommendations, hotel recommendations, movie & streaming suggestions, to what’s missing in your refrigerator, intelligent cars, transaction guards, smart nutrition bots, stock predictions, and whatnot. AI is everywhere. In fact, it helps you in even finding the perfect date.

Maybe, in the near future it can tell you about the fastest route to success as well, Lol. Kidding. 

With AI startups raking in $68 Billions in 2021, with all the R & D, our reality doesn’t seem to be that far from The Star Wars or The Matrix. Engineers have already started claiming their AI tools to be reaching sentience. Startups, enterprises, and SMBs are all guns ablazed with new AI developments, innovation, and patent filings. AWS is no behind. In fact, AWS is a torchbearer for empowering companies to architect AI solutions in the cloud.

Read this insight to find how you can leverage AI focused PaaS/IaaS offerings of the AWS for architecting AI solutions in the AWS cloud, and help accelerate digital transformation of your org.

AI solutions that can be built in the AWS cloud

Amazon web services offers multiple AI PaaS & SaaS technologies for developing AI use cases which are designed to seamlessly integrate with other infrastructure centric services from AWS like EC2, S3, Aurora, DynamoDB, and so on. 

So, for example, let’s say that you have built your streaming application in the AWS, and you’re storing your user activity data in the DynamoDB.  Now, you can use AppSync to seamlessly integrate Amazon Personalize (which is a highly sophisticated recommendation engine) and Amazon DynamoDB for recommending user-personalized content recommendations and ad placements. This helps you in delivering delightful customer experiences, and subsequently improves customer loyalty in the process.

Here are some common AI use-cases for which AWS could be a good fit:

AI Computer vision applications

computer vision solutions development in the AWS

Computer vision is analogous to how our eyes & brain work in tandem to process what we see. Amazon Rekognition, AWS Panaroma, and ALS from the AWS AI stack can help you in architecting & deploying computer vision (CV) centric AI solutions in the cloud. With computer vision you can improve the security of public & private premises by analyzing image/video sequences from multiple cameras in real-time, proactively monitor & manage assembly lines, warehouses, improve efficiency of autonomous robots, embed image search functionality in your ecommerce store, or help medical researchers in diagnostics by detecting patterns in the medical images and maybe facilitate them in innovating cures for deadly diseases. There is so much more.

Intelligent Legacy Docs Digitisation

Manual document processing is painfully slow, prone to human errors, and dead boring. At scale i.e., when we are talking about digitizing millions of invoices, medical reports, KYC forms, insurance claims, or purchase orders, manual document processing can take years and can cost millions$. AWS AI stack is your savior.

AI led document data extraction solution

You can exploit Amazon Textract, Amazon A2I, Sagemaker, and AWS comprehend to design end-to-end document processing solutions. Saving millions of dollars and human-hours! 

Fraud identification and/or prevention

Duplicate profiles, real-time identity verification, identification of fraudulent transactions, safeguarding credit cards, and screening reviews to identify fake positives are some common use-cases of AI to protect businesses from rogue users. Again, let’s say you are storing transactional data in AWS S3 bucket, Amazon Sagemaker can be used for anomaly scoring using Random Forest machine learning algorithms. Similarly, you can use multiple other libraries for fraud classification scores. Stream these processed information into some other storage (like S3) and integrate it with data analytics & visualization tools (e.g., Amazon QuickSight) for further querying, report generation, and other use-cases.

Get in touch with our AWS AI consultants to architect AI focused solutions for any of the following AI use-cases:

  • Computer Vision Applications
  • Legacy doc processing at scale
  • Fraud detection & prevention
  • Personalized product and/or content recommendations
  • Personalized AI led gamification of CX
  • Intelligent DevSecOps
  • Intelligent BPO operations
  • NLP & speech recognition apps

AWS AI Stack for Your Business

On a high-level, businesses use AI & ML to cut costs, improve customer experience, enhance employee productivity, augment ops efficiency, business agility, business resilience, process transparency, and to automate boring manual processes. You can use a suite of AI Paas/ IaaS/SaaS offerings from AWS to build intelligent AI solutions in the cloud.

Here we list the AI technologies that AWS offers:

Amazon Sagemaker

Amazon is a fully-managed machine learning as a service (MLaaS) tool from AWS. It’s like a hosted Jupyter Notebook in the cloud. You can easily deploy ML models and build AI solutions at scale with AWS sagemaker. It comes in three different packaging i.e., Sagemaker Canvas, Sagemaker MLOps, and Sagemaker Studio. While Sagemaker Canvas is used for designing prediction focused ML solutions using a visual interface, Sagemaker Studio & Sagemaker MLOps are more about getting your hands dirty with the scripts to build, train, and deploy ML models.   

It is optimized for using frameworks like Tensorflow, Pytorch, Scikit Learn, and Hugging Face. Sagemaker offers ready to use container images for more than 15 ML algorithms including XGBoost, ResNet, DeepAR, k-NN, LDA, and regression. 

Besides, it is being used by Intuit, Lenovo, Aurora, Thomson Reuters, Hyundai, and GE healthcare. 

Amazon Panorama

AWS Panaroma

AWS Panorama works on top of computer vision models built with AWS Sagemaker or similar technologies to design computer vision solutions on the edge. AWS Panaroma appliances are integrated with one or multiple onsite cameras to run CV models on the streams generated by these cameras in real-time. The insights/results/predictions are channeled to Amazon CloudWatch or Amazon S3 for analysis, or it is looped into line-of-business applications to take immediate actions, or to ensure smooth workings of automation workflows.

Amazon Personalize

Amazon Personalize is again a fully managed MLaaS offering. This is widely used for customizing user experiences on the home page, boosting upsells and cross sells by optimizing marketing campaigns with sharp user segmentation & personalized focus on individual users, intelligent content recommendations for better audience engagement. Personalize can be easily integrated into your marTech, web app, and mobile app with API interface. GetRecommendations API and GetPersonalizedRanking APIs are two popular Amazon Personalize APIs for generating product/content recommendations and re-ranking products in real time.

Amazon Augmented AI (A2I)

Amazon A2I

Amazon Augmented AI (A2I), as apparent in the image, helps you build scope for humans to audit/review low-confidence predictions made by AWS AI PaaS/IaaS technologies. This again streamlines the process of prediction review, cuts the deployment time to days, and ensures continuous evolutions of the models and prediction efficiency. It is easily integrable with the entire spectrum of AWS AI technologies including AWS’s RekognitionTranscribeComprehend, and Translate services. 

Amazon Textract

AWS Textract overcomes the limitations of OCR by using it in tandem with ML algorithms to intelligently extract data from scanned copies of handwritten documents, forms, and tabular data. Unlike OCR, which needs customization when the format of the document or type changes, AWS Textract intelligently establishes relationships between diverse data sets and cuts down the ‘scanning to insights’ time to hours from days. It is also used with A2I to audit prediction efficiency. Texteract is highly useful for healthcare, finance, and government organizations.

Amazon Comprehend

Amzaon Comprehend

Amazon Comprehend uses Natural Language Processing (NLP) to extract valuable insights from your apps database/documents. Using AutoML, it performs custom entity recognition to spot & segment entities like insurance policy numbers, legal case number, invoice number, etcetera. You can also build sentiment analysis capabilities, personally identifiable information (PII) redaction features to protect financial information or contact information in BFSI & healthcare documents respectively. All these capabilities are easily integrable with APIs and can be consumed in JSON format. 

Similarly, we have multiple other AWS AI technologies catering to a wide range of industry applications:

  • Rekognition is used for computer vision applications: Face detection, image labeling, live video streams classification [ecommerce package delivery, or healthcare operations], content moderation [akin to Twitter’s sensitive content notice].
  • AWS Lex uses NLP for smart chatbot integrations & to improve CX with virtual assistants.
  • AWS Transcribe, as the name goes, transcribes videos, conversations, and calls to gain insights from them. It’s used to build speech to text AI solutions.
  • AWS Polly is the exact opposite of Transcribe, and is used to build text-to-speech solutions. Great for creating content focused solutions, and E-learning app features where text notes are converted to voice notes.

The list is long.. Amazon Kendra, Forecast, HealthLake, CodeGuru, and so on. Get in touch with our consultants to find out the right stack of AI technologies for your business use-cases.

Build AI apps with Codewave

Codewave has always been a trendsetter when it comes to innovating with new age technologies, designing customer journeys, and/or accelerating organizations on their route to digital transformation. 

Using the above set of PaaS/IaaS/SaaS AWS technologies and our design thinking practices, we help businesses to envision, plan, and architect artificial intelligence projects with zero friction, high scalability, and high usability.

  • Take a look at some of our works out of the 350+ apps that we have built in the past 9 years,
  • Explore the complete spectrum of digital services we provide to help you maximize the impact you’re creating, and
  • Contact our consultants for a discovery call on how we may collaborate to innovate together.

Cheers to innovation & growth  

Onwards & upwards!

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