Construction ERP Software

Projects Overview

The IMAPS ERP is a software-as-a-service (SAAS) model with complete customization. This enterprise resource planning (ERP) system helps users avoid costly mistakes, catch estimating errors and most importantly save millions of dollars on projects. Take advantage of AI based progressing/forecasting, estimation and cost control. IMAPS-ERP is designed with a project management system which feeds the financial system module.

A program which takes the activities of most corporations and aligns them to provide strategic, managerial and financial intelligence.

Its a mobile app that allows contractors to:

• Progressing & forecasting
• Estimation and budgeting
• Project costing
• Document management
• Change management
• Punch-list & issue management
• Payroll and timesheets
• Equipment tracking
• Cost codes
• FIWPs

The implementation of this construction ERP is easy, user friendly, swift and cost efficient. Switch your focus from daily tasks to a strategic business intelligence model. Implemented in weeks with no impact to current systems.  IMAPS Construction ERP systems cost millions of dollars to companies from IT architectural design to implementation and maintenance. The return on investment would not be the same for SMEs that require a tool that provides traceability as well as management capabilities. IMAPS Construction ERP provides its users with the tools and intelligence of top competitors, but at a fraction of the cost of implementation.

Working Process

Step 01

Research

Requirement gathering, stakeholder meeting, details specifications, wireframes

Step 02

Development

Develop architecture, design, develop and test

Step 03

Deploy

Deploys software as a service to production environment, provide support and ongoing maintenance and enhancements.

Conclusion

Digital Fractal developed a software as a service product for a construction business to streamline business operations, provide intelligent signals and reporting and accountability/traceability within its organization. Utilizing machine learning from past data, the software enabled estimators to better estimate new projects.