qCloudy

qCloudy was hired by an agriculture leasing company to modernize their information system by implementing an OCR module to automate the processing of financing applications. The project involved the development of a solution for recognizing multilingual text from PDF documents and images, integration with an AI model for intelligent document classification, and the implementation of the entire architecture based on AWS. The team demonstrated deep technical expertise in the field of OCR and cloud technologies, met deadlines, and responded flexibly to the company's requirements. The implemented solution significantly reduced the processing time of applications and reduced the proportion of manual labor.

qCloudy was contracted by ALTEL/TELE2, a leading mobile network operator in Kazakhstan, to develop and implement an AI-powered bot for audio file analysis. The project involved developing a complete AI-powered bot for audio file analysis built on a cloud-based infrastructure for scalability and reliability. The solution included a robust Speech-to-Text (STT) API, a powerful Large Language Model (LLM) for processing the transcribed text, and a secure and efficient data pipeline for managing the flow from audio file upload to final summary generation. qCloudy also developed a clean, intuitive web-based interface where users can easily upload audio files and view the resulting summaries.

KPMG, a professional financial and consulting services company, engaged qCloudy to deploy and configure a complete AWS-based infrastructure. The project, named KZ-KPMG-AWS, involved architecture design, infrastructure as code preparation, deploying multiple environments, and setting up CI/CD pipelines. The work covered configuration of networking components, Kubernetes clusters, monitoring and logging systems, as well as integration with corporate services. QCloudy demonstrated exceptional professionalism throughout all phases of the project.