Architecture Review and Refactoring for a QA technology company

A SaaS platform that offers quality assurance solutions to contact centers, engaged with us to have their platform reviewed and re-architected/re-factored to fix platform’s performance issues, functional bugs and to add new features.

We analyzed the system, code base, APIs, background jobs, and database, identifying bottlenecks and proposing a cloud-based solution. Using AWS Lambda, ECS Fargate Tasks, Azure Logic Apps, Azure Data Factory, and Azure Functions, we built a serverless ETL and data processing platform that stores and processes massive audio data, utilizing third-party machine learning and NLP services. We created missing documentation, analyzed code quality, and optimized cloud utilization. Our optimized team re-architected the system, refactored buggy code, and implemented ETL pipelines in Azure to manage data and audio processing from multiple sources.

The team successfully migrated the old transcription process, which was using Deepgram 3rd party services and background jobs running on VMs, to Serverless architecture. The new transcription process uses AssemblyAI and provides better transcription, sentiment analysis and deeper insights. The automated pipeline framework is scalable to allow the addion of more clients. Additionally, the team enhanced legacy components by solving bugs, refactoring inefficient code and optimizing complex SQL queries which were causing slowdown of the whole platform.