A Midwest company has manufacturing hubs worldwide. They produce product packaging for many multinationals. They aim to maximize revenue by forecasting client demand and availability of resources. To accomplish this, the following components were built:
These systems allow the company to plan and optimize their manufacturing resources on a global level.
A logistics and transportation company needed to track packages, images, do advanced driver tracking, and deal with exceptions. They were faced with a huge database that would require a large investment in user identification alone.
ThinkTech designed and developed a server-less mobile application to work on both Apple and Google Play. The solution employed Amazon Web Services for authentication, real time tracking and shipment updates. The system includes the use of RFID, barcode scanning, signature capture as well as image and video uploads. ThinkTech designed a hybrid solution by using API’s to update query and integrate with the on-premise AS/400 DB2 based logistics system.
ThinkTech worked in close collaboration with the client to ensure ease of integration with the company’s legacy system thereby eliminating the need for any additional investment by the client. The system included the following technologies:
This Financial Management company based in Virginia manages the finances of the most popular and high earning athletes, personalities and entertainment celebrities. They needed to provide a system to generate client statements from their accounting system and deliver them to a secured web portal.
An SAP BI solution was implemented that was fully customized to generate individual client statements, cash flow requirements and to provide for ad hoc mass report generation.
The project helped the financial management company provide accurate accounting and delivery of reports and analytics to assist customers for Financial Counseling and management.
We consolidate IOT data using Azure Databricks into resources where the data can be presented using Power BI reports. We also design Power BI dashboards and do software development using JavaScript frameworks and other web technologies. The team also uses Python and Spark for analytics and data transformation, writing scripts to manipulate data coming in from various datasets and data sources.
The objective of the project is to transform the company’s manual and static reports to a more dynamic one. We are doing so using Power BI and the ETL tools to architect and present the data on a more modern platform that allows users to interact with their reports.
We provide Business Intelligence reporting and data modeling using the SAP Web Intelligence and SAP Information Design Tool. In addition, we also do Software Development and assist the client with Forecasting.
The team designs Universes from the data lake using SAP Information Design Tool. They also develop reports using SAP Web Intelligence for business users. As part of their day-to-day activities, they interact with the client to gather requirements for their reporting needs.
In addition to this, the team has developed two apps for internal use with the client. The team also maintains Python scripts used for ARIMA Model forecasting.
The first app was developed with Java and React. Java was used for APIs and the backend, while the frontend was developed using React. The app allows the client to manage its pool of contractors from one portal.
The app covers the following:
The second app was developed in Java and is used by Commercial (clients of Matthews International) to modify data generated by the ARIMA Model that they believe does not accurately represent output in the coming 6 months.
We have developed a web application to advantageously assist with the automating of the overwriting process for a real estate firm. This app is constructed using AWS Services for Artificial Intelligence, React and Java.
The frontend of the webapp is developed in React and the backend in Java. The webapp is hosted on AWS and allows underwriters to create deals, evaluate deals, process supporting documents, and generate an offering memorandum for a deal. The app leverages Amazon Textract to scrape documents (PDF, Excel, etc.) and grab relevant data by referencing a dictionary of terms and outputs the data in tabular format. The data is sent through a manual review process to improve the accuracy of Textract in identifying data in the supporting documents needed to generate an offering memorandum.
The SAP META Xplorer, which was developed using Java, conveniently connects to SAP and utilizes available APIs to obtain and report on the metadata of an SAP Deployment.
The app was developed in Java and utilizes available SAP API’s to collect metadata on the SAP deployment for Administrators to review.
The data collected consists of:
– Users and User Groups
– Reports
– Universes (data models)
– Public Folders
– Personal Folders
– Provide AWS operational support
– Create virtual infrastructure
– Support VDIs
– Optimize AWS environment and servers
– Troubleshoot infrastructure issues
Provide reports on usage and performance on the AWS environment.
