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As InterWiz’s adoption grew, the customer chose to migrate the platform’s AI capabilities from Azure OpenAI to Amazon Bedrock to align with its broader cloud strategy.

In the fast-paced world of software development, effective release management and controlled deployment are crucial for delivering high-quality products to end-users.

Our customer, a fortune 500 company consisting of more than 70,000 employees, aimed to develop a video streaming platform to broadcast their tech events to viewers all around the globe. In achieving this target, they faced two primary hurdles from a testing perspective:

As children navigate the digital world, they are increasingly exposed to online threats such as explicit content, cyberbullying, and unsafe interactions. Safe Kids AI, committed to protecting children's online activities, sought to build a secure and scalable monitoring application. The goal was to empower parents with tools to oversee their children's online interactions, helping to ensure their mental and emotional well-being.

A greenfield customer aimed to establish a robust infrastructure that could facilitate the automatic and intelligent building and deployment of applications.

A customer faced escalating AWS infrastructure costs with limited visibility into resource usage and expenditures. This prompted concerns about continuing AWS services due to budget constraints. There was an urgent need for a solution that not only reduced costs but also provided greater transparency and control over spending.

In a landscape where software quality directly impacts business success, our client faced a pivotal challenge: the need for early bug detection and a significant reduction in manual testing efforts. Testing late into the development lifecycle not only delayed deliverables but also inflated bug-fixing costs, thus impeding timely project completion and affecting time to market.

Traditionally, enterprise networks were designed for local application access, with centralized security measures. This setup, however, became inadequate as enterprises expanded and increasingly adopted SaaS applications. The conventional model of routing all traffic through a central security stack was not only inefficient but also hampered the user experience due to increased latency and reduced network performance.

Ensuring that a product is thoroughly tested before moving to production is crucial for every product, regardless of the industry segment. The traditional approach of setting up staging environments if often time-consuming and resource-intensive, leading to delays in product testing and deployment. The need for a quick, cost-effective solution to streamline the staging environment setup was paramount.