Retail Business

One of our clients wanted to speed up the identification, tracking and correction of errors. The requirement was to provide a complete picture of application performance. We've built a solution using a combination of New Relic, Splunk, and Opsgenie to provide a custom dashboard and alerting system that gives a clear view of various application performance and log metrics.

As a result, root cause analysis speed was reduced from an average of 5 hours to 2 hours for P1 issues. Log analysis has become a key asset for the team to forecast and proactively fix problems, helping maintain a more stable system.

One of the top Middle Eastern financial services providers wanted to significantly reduce costs by increasing the current time to market, ensuring the timely release of high-quality products, ensuring uniformity across LOBS in processes and procedures, and retention of knowledge relevant to a particular region. We had formed a team to handle all testing requirements across the organization for this, developed a framework for automation that can be used with various tools and programs, centralized storage for function libraries and reusable parts that hastened testing cycles and ensured efficient governance, knowledge management, and resource use. Total cost of quality decreased by almost 42%, Automation and reuse reduced testing effort by 40%, Reduced test cycle time by 35% resulting in significant improvement in time to market.

E-Commerce Website

One of our clients in the e-commerce industry requested automated functional and regression testing for the entire E2E e-commerce flow as well as the ability to execute the automation test suite across several mobile and browser OS platforms. For this, we employed a whole open-source Selenium-based internal automation framework. Agile's functional automation cycle was shortened by 1 week. Due to the extensive testing coverage achieved through coordinated implementation and framework advancements, the product team's confidence levels increased when they were able to quickly deploy their code into production with full test coverage. By using Jenkins and Sauce Labs for parallel execution and OS coverage with a single click, we were able to perform multi-browser and OS coverage.

There are an exponentially growing number of ICOs being issued. In such circumstances, the number of fraudulent initial coin offerings (ICOs) is also rising alarmingly, and investors frequently struggle to distinguish between genuine and fraudulent offerings. The goal of one of our clients was to solve this issue. For that, we created a platform that makes this visible by combining AI and Blockchain. Based on market patterns and historical data, the platform uses AI algorithms to make investing judgements. The bots' ability to have a purchasing and selling plan using NLP and machine learning boosts the users' profit margins. The platform enables investors to safely aggregate their funds across various ICOs. The ICODO platform buys and sells ICOs using algorithms, which helps investors avoid fraudulent ICOs and maximize their returns. Using Blockchain, the investors will have constant access to their portfolio and assets.

IDEOREO

One of our top Indian clients wanted to organize the country's grey-collar workforce by creating a blockchain-based HR solution. The platform's goal was to provide a one-stop shop for all issues in HR involving payments, compliance, fraud, and taxation. The idea attempts to establish a national labor record that can be accessible by all businesses nationwide via Blockchain. The data is saved in a blockchain, therefore creating a fake profile is not possible. As a result, middlemen's involvement in the labor supply is restrained. The solution also deals with difficulties like issues in identification verification, transparency in the work hour cycle, falsified recruiter credentials, payment problems, determination of recruit skill level, etc.

Convolutional neural networks from computer vision are used in this approach, which was developed to facilitate signature fraud detection and signature detection. Our neural network, which was based on the VGG-16 neural, a prize-winning model, aids in the very accurate detection of signature fraud. Any field where sensitive signature data is present could benefit greatly from using this application. The model can be applied in real-world settings since it can learn from a small number of training photos.

Product Finder

The items for an E-Commerce platform are manually classified into categories, but with this Al platform, the E-Commerce vendor may greatly simplify this work. This application has been designed to be very scalable. A small amount of training data would be required, and after that, the system would be capable of handling product classification. To complete this objective, the method combines Computer Vision and Text classification. Tensorflow serving is used by the product to scale up to handle massive amounts of incoming data. Any domain can easily adopt the application.