The AWS ecosystem is an invaluable asset for enterprises driving their digital transformation. While the AWS Cloud infrastructure is powering a huge slice of enterprises, there are several other AWS solutions, especially in the realm of computation and machine learning, that’s enabling enterprises to leverage emerging technologies.
Here’s a look at some interesting projects and PoCs that Srijan has delivered for enterprise clients, using AWS solutions.
Chatbots powered by Amazon Lex and AWS Lambda
As a leading provider of intelligent cleaning solutions, the client wanted to be able to analyze and optimize the performance of their products. They had a set of data visualization dashboards that track this data in real time. However, these were not easily accessible and involved some effort before stakeholders could extract relevant insights.
The solution was to build enterprise chatbots that could deliver the same insights without taking up too much time or effort on the part of the client stakeholders. They could just type their query into the chatbot, and receive an appropriate response.
Srijan leveraged Amazon Lex as the core conversational interface framework to design the chatbot. Lex’s deep learning functionalities enabled the chatbot to identify the intent behind a particular questions, understand the context, and give back an appropriate response.
The other key solution used was AWS Lambda, that handled the backend extraction of data form the client databases, and computation to generate the correct response. The business logic defined atop Lamba determined how the raw data from various sources would be interpreted and presented to the user as a final answer.
Other AWS services used were:
- AWS Cognito for user authentication
- AWS Translate to ensure the chatbot could be used by client stakeholders in any location
- Amazon S3 to store relevant asset images and performance graphs that could be accessed solely by the chatbot users.
Video Analytics powered by Amazon SageMaker
The cleaning solutions enterprise was also receiving increasing complaints around their floor cleaning machines not performing as expected. The client wanted to have detailed logs of machine performance across all locations, so validate or refute these customer claims, and prevent unwarranted expenditure on recalls and repairs.
Srijan proposed a video analytics algorithm capable of identifying the machine and verifying its performance at given locations. The approach was focussed on recording real-time footage of the machines operating at different customer locations and then automatically analyzing the video feed to identify and verify if the machines are performing as expected.
This was achieved with a deep learning model designed to analyze video feed data. The key objective of the model, built on convolutional neural network, was to accurately identify the machine in a video stream at 5 second intervals. These sightings are then timestamped and put together in a JSON file. This created a continuous log of whether a machine is working or not, in any given location.
Amazon SageMaker was the core solution used for this model. As a managed platform, it allowed for:
- Creating the deep learning algorithm, with TensorFlow
- Data augmentation and training the algorithm to accurately recognize the machines in a video stream
- Quick and efficient scaling of training data to create a more accurate machine learning model
Once the model was in place, Srijan used Amazon S3 and AWS Lambda to create the workflow for collecting video feed from various customer locations, analyzing them, and creating detailed logs of machine performance.
Enterprise Data Analytics Platform with AWS Lambda
OnCorps offers PaaS for insight into enterprise data, to make better decisions using predictive analytics, machine learning and peer comparison. They wanted to create a platform that can do a lot of the heavy lifting when it came to data - right from gathering, to processing, to analytics and visualization.
While the platform was built on Drupal, Srijan leveraged a host of AWS solutions to deliver some powerful functionalities:
Amazon EC2: This offered an easily scalable and cost-effective computation solution. It gave the ability to run data analysis, compute workloads to aggregate data, as well as deliver predictive insight.
AWS Lambda: The frontend interface of the platform needed structured data to work with, preferably in JSON format. Lamba was used to transform the data coming in from various sources into a standard format.
Amazon S3: This was used to host the single page application built on AngularJS. S3 was also used as storage for all files and content assets for the platform.
AWS Cost Explorer: One of the Srijan team’s primary objectives was to keep product development costs on track. AWS Cost Explorer was used to get a clear visualization of operation costs across all solutions, and optimize the budget as much as possible.
With these solutions in place, OnCorps was able to roll out a scalable platform with >99% performance reliability across enterprise customers.
Cloud Native Storage with Amazon S3
TheRecordExchange (TRX) offers a SaaS-based workflow management application to capture and access recordings of legal proceedings. Their business model is dependent upon frictionless uploading and downloading of text and media files. The application frontend is designed so that transcription agents can easily upload files of legal proceedings, and customers can download them at will.
Given this, they needed a cloud-based server that could efficiently manage all file-related requests on the applications, and robustly render them on the frontend.
With Amazon S3, an object storage solution, Srijan was able to deliver a flexible clou-native storage for TRX. S3 enabled:
- Addition of any number of files to the application, without worrying about capacity constraints. Since the application layer didn't have to handle file processing, it was lighter and delivered a better user experience.
- Dynamic spacing, which allowed TRX to scale up or scale down space usage as and when required. With no minimum usage requirements and availability of on-demand usage, S3 proved to be a highly cost-effective solution for the client.
Srijan is an Advanced Consulting Partner for Amazon Web Services (AWS). It is currently working with enterprises across media, travel, retail, technology and telecom to drive their digital transformation, leveraging a host of AWS solutions.
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