AWS Powered Solutions

Increasing speed & agility

R Systems’ AWS experts & solution architects helping clients succeed with AWS platform, increase the pace of innovation & decrease cost with AWS powered solutions.

AWS Solutions, designed by our architects, are operationally effective, performant, reliable, secure, and cost-effective; and incorporate architectural frameworks such as the Well-Architected Framework.

Every AWS Solution comes with a detailed architecture diagram, a deployment guide, and instructions for both manual and automated deployment and these can be customized for specific use cases.

  • Document Classification
  • Conversational Bots
  • Real Time Speech Analytics
  • Table Extraction
  • Face Recognition Solution
  • Image Classification Model
  • Image Segmentation Solution
  • Recommendation Model
  • Form Extraction

A distinctive document classification model that quickly analyzes and tags documents (such as newspaper articles, web pages, advertisement copies, blogs, articles, emails, and social media updates) for easier discovery.

R Systems leverages Amazon SageMaker to deploy its Document Classification model on embedded systems and edge-devices as well as Amazon SageMaker image classification algorithm to support multi-label classification.

Our distinctive Document Classification tool is applicable across an extensive range of processes including customer support, legal support, branding & advertising, scientific publication, and human resource.

Equipped with advanced and highly-responsive AI, our voice-activated bots and text-based Chatbots can effectively handle diverse patient requests across a broad spectrum of activities both in the clinical and the administrative areas.

R Systems' Chatbot/Speechbot utilizes Amazon Lex and Amazon Transcribe to provide deep functionality and improved flexibility of natural language understanding (NLU) and automatic speech recognition (ASR). It also utilizes AWS Polly – a text-to-speech (TTS) service - to synthesize speech. This enables organizations to build bespoke bots for highly engaging user experience.

In addition, our platform leverages AWS Lambda to offer serverless computing platform & Elastic Compute Cloud (EC2) to enable scalable compute capacity.

An all-inclusive real-time speech analytics solution- Anagram - enables global organizations to transcribe and analyze customer interactions across marketing, selling and service channels. Powered by advanced AI services of AWS, our speech analytics platform can analyze and discover customer sentiments; identify specific customer intentions and behaviours; determine and help resolve core issues by analyzing customer-agent interactions; and develop standard best practices intended to streamline overall call center operations.

The solution is applicable across a broad spectrum of use cases:

  • Voice of Customer (Voc) Analytics: Leverages Comprehend to analyze customer sentiments and give sentiment scores, distinguishing customers into high detractors, medium detractors, passives and promoters categories.
  • Call Categorization: Classify transcriptions using custom classification API of AWS Comprehend to determine the types of call your business is receiving.
  • Agent Scorecard: View and compare agent performance, spot knowledge gaps, best-performing teams and adherence to pre-defined goals.

A robust AI-enabled data extraction tool that makes it easier for people across business functions to detect and extract actionable information from tables. The solution leverages AWS Textract to extract tabular text and data.

Powered by advanced AI services of AWS, our solution can expeditiously extract table data from virtually any document, reducing manual extraction while accelerating the turnaround time.

The automated table extraction tool processes entries from simple to intricate tables, deriving value from the data your business is now amassing.  The solution enables business to upload the extracted data into database, all without altering its tabular structure.  

An all-inclusive face recognition solution that provides a fast, accurate, and non-invasive means for identifying human faces. It maps distinguishable facial features, patterns in the visual data, and compares new images and videos in the extensive libraries. The solution leverages neural networks and deep machine learning to make the technology a usable reality.

It utilizes Amazon Rekognition to recognize faces in images and videos; BOTO 3 (SDK for Python) to access object-oriented APIs; and Python & OpenCV/ CV2 to activate and capture real-time videos from the camera.

The tool effortlessly recognizes multiple faces simultaneously, including emotions, age, and gender at an unparalleled speed and scale. Buoyed by ironclad security system, R Systems' high-end facial recognition application allows users to add new tags within the current database for any existing or add-on face right away.

A personalized and responsive image classification model to identify images and objects from rich media (digital image files). It offers enhanced search capabilities to identify hundreds of classes of objects - including people, activities, animals, plants, and places and categorizes images based on metadata, colour and other factors.

R Systems’ Image Classification Model is underpinned by deep neural nets that can learn higher-level representations (features) of input images. It utilizes Amazon Rekognition to identify objects, people, texts, scenes, and activities in images, as well as to detect any inappropriate or copied content.

Our Image Classification Model can be customized to fit into your unique business requirements. You can feed the platform with your unique datasets and start training it to work the way you want. R Systems leverages Amazon SageMaker to deploy this customized model through Amazon SageMaker image classification algorithm.

An intuitive Image Segmentation Solution that helps partition an image input into multiple segments for simplified image analysis. Backed by advanced AI services of AWS, the tool partitions a digital image into fragments based on various factors like pixel intensity value, colour, and texture. The solution leverages AWS Semantic Segmentation to collectively assign label(s) to every subdivided segment in an image surrounded by a bounding box.

In addition, it utilizes AWS Rekognition for detecting labels and categorising existing segmentation algorithm into region-based segmentation, data clustering, and edge-base segmentation.

Our Image Segmentation solution can be used across a broad spectrum of industries, including Robotics, Traffic Control System, Sports Analytics, Video Surveillance, Medical Imaging and Diagnostics, Autonomous Vehicles, Livestock Management, and Media & Marketing.

A Sagemaker R Kernel using customized collaborative filtering algorithm that delivers intelligently-generated product recommendations by extracting hidden insights around historical user-product interactions. It digs into similar type of products leveraging historical user ratings through correlation pointers.

Driven by machine learning, our interest-based recommendation solution leverages AWS Sagemaker to provide personalized recommendations for customers, and item based collaborative filtering to provide recommendations during a session. Moreover solution sends email notification alert to the user around product recommendation if it finds strong affinity and relationship with the user leading to higher sales for the business.

Businesses can predict what they want next; dynamically present tailored recommendations; and drive innovation on all fronts - integrating AWS SageMaker trained model into their existing process.

An automated data extraction solution that enables businesses to extract key-value pairs from scanned documents in no time. It massively cutbacks manual efforts required in processing forms and other documents into digital formats.

R Systems’ key-value based extraction leverages AWS Textract to extract text and data from virtually any document, AWS S3 to provide scalable cloud storage.

Form data extraction tool identifies contents of fields in all kinds of embedded forms, keeping the composition of extracted information completely intact.

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