Application Modernization for Cloud

Vertisystem architected and built a new cloud-based application to replace the existing MS-Access application. Functionality was expanded to include more commitment types, provide greater ability to track and report on commitments and automate integration of data from multiple sources providing a single-source of information for all of the organizations funding commitments. The new application is a web-based application deployed in the cloud and based upon the following technologies: ● ReactJS; HTML; CSS; Angular. ● JAVA 11; Spring Boot; Python; SQL; APIDriven; Sonar Qube. ● PostgreSQL; Oracle; MYSQL. ● Source Clear / OAuth/ SAML/Discovery Page. ● Google Cloud Platform; AWS; Azure. ● Big Query; CloudSQL. ● Google StackDriver/Kubernetes; Docker. ● Google Compute Engine (GCE); Google Cloud Storage (GCS); Google AppEngine (GAE). ● AWS EC2 S3; MSFT Azure; Google Fire Base.

A SaaS Solution

Our client’s software solutions are typically highly complex with specific interfaces and requirements, hence the Vertisystem team has to familiarize themselves with not only Client’s tech environment but also with the environments of both the retailers and installers in order to create effective integration strategies. After going through an initial discovery phase, the following technical tasks were identified as required to meet the project goals. ● Integration of various 3rd party applications and data sources through RESTful API development and integration. ● Development of a custom parsing tool to glean information from 3rd-party forms such as Purchase Orders; Invoices; Payment Remittances; Job Order Details & etc. ● Designing & architecting solutions around existing platform limitations such as lower frequency of data upload and download from 3rd party sources. ● Creation of a system to alert concerned stakeholders regarding the data exchange and other such events through various channels such as email & SMS. ● Optimizing the technology stack such as data storage so TCO can be brought down.

Cloud ML – Forecasting Booking Pattern

● Vertisystem assisted our client in the design & development of a scalable, automated cloud-based Machine Learning solution which forecasts the demand & booking pattern leveraging the client’s existing GCP Environment & Looker. ● Vertisystem contributed to solution architecture, feature engineering, data preparation, batch prediction, data refresh automation and model evaluation/retraining processes. ● The complete solution provided a model using Cloud AutoML. In collaboration with the business users, Vertisystem developed Looker models, reports & dashboards which interact with existing revenue data & provides key insights using the forecasted data.