Overview
Maverick is a sales analysis tool that analyzes procurement history and forecasts demand for US government departments' solicitations. It helps to search and filter the procurement history and also recommends relevant solicitations based on processed data. It integrates SOAP-based APIs to fetch data, utilizes SpringBoot for the backend, and ReactJS for the web app.
Maverick, the sales analysis tool developed by BinaryTouch, provides comprehensive solutions for analyzing the procurement history and forecasting demand of US government department solicitations. The primary goal of Maverick is to recommend relevant solicitations based on the processed data and to help clients to bulk bid for solicitations.
Requirements
Our solution
Analyze the history of procurements and forecast demand for US government departments' solicitations.
Develop an advanced data analysis module that processes the procurement history and applies forecasting algorithms to predict demand for upcoming solicitations.
Integrate SOAP-based APIs services to fetch procurement history and demand forecast data from multiple sources.
Establish seamless integration with SOAP-based APIs, enabling the system to fetch and aggregate procurement history and demand forecast data from various sources, ensuring comprehensive and up-to-date information.
Develop a recommendation engine based on procurement history to recommend upcoming contracts.
Build a powerful recommendation engine that leverages machine learning techniques and analyzes the procurement history data to provide accurate and personalized recommendations for upcoming contracts, considering factors such as relevance, budget, and department requirements.
Implement a semi-automatic bulk bidding functionality for easy bidding on recommended solicitations.
Develop a user-friendly interface that allows users to review the recommended solicitations and enables them to place bulk bids with minimal effort. The system should provide pre-filled bidding forms and streamline the bidding process, saving time and increasing efficiency.