The client needs automation for manual procedures in handling bankrupt clients, as well as for document management and payment recommendation platforms.
Java, Spring Boot, Java Persistence API(JPA), Hibernate, Gradle, Google Cloud, Openshift, Swagger
The client requested the development of applications/microservices to automate manual operations. A backend application was needed for lawyers to upload details of bankrupt clients into legacy systems. Additionally, a portal for clients to upload data for third-party vendors was required to be improved. For the payment recommendation platform, the creation of a base architecture was expected to provide payment options for small- and medium-sized companies.
A significant challenge in automating systems that incorporate legacy components is the effect of legacy behavior on the performance of developed microservices. In the banking industry, security is prioritized above other considerations, requiring the implementation of encryption in transit for data stored in an Oracle database.
Datics assisted the client in achieving their objectives in a timely manner. To integrate with legacy systems, a circuit breaker was implemented from a distributed systems perspective and document handling was automated using scheduled jobs. To handle potential issues from legacy integration, asynchronous computation was implemented. For security, encryption in transit for database transactions was implemented at both the application (client) level and the database server level.
All application development was successfully deployed and end users could use the services smoothly. The implemented encryption was a first for the client and has since become a standard in all subsequent backend applications for encryption in transit.
Industry: Medical Technology
Technologies: Azure Kubernetes service, Terraform, Azure DevOps pipeline
The client must store vast amounts of data in various formats from multiple sources in a unified data platform, accessible to machine learning engineers and data scientists within the organization for the development of machine learning applications and data analysis.
Industry: Automotive
Technologies:Java, Spring Boot, Java Persistence API(JPA), Hibernate
Technologies: Azure Functions, Github Actions, Python | Flask | Pytest, Microsoft LUIS
We developed a voice-based AI system utilizing voice recognition and natural language processing to communicate with customers in a car.
Technologies: Gluoncv, opencv, decord and Python
A client in the medical technology industry has a requirement to protect the anonymity of individuals whose images or videos are being used.
Technologies: Grafana, Prometheus, Azure Monitor, TorchServe, Docker
The medical technology client aims to deploy their machine learning models on Azure cloud for active use by consumers.
Get in touch with our experts and start your journey towards business evolution, innovation and profitability. Upgrade your company with our cutting-edge IT infrastructure and data management services. Contact us today to schedule a consultation.
Your Name
Your Email Adress
Your message I agree with Privacy Statement and Terms of Use.