Development of a Cloud-Based Data Capture and Risk Analysis Platform for Construction Advisory Services

The client faces challenges in scaling their risk mitigation services due to limited and inefficient data collection methods on construction sites. Their existing application lacks essential features such as security, mobile support, and scalability, which hampers their ability to deliver timely insights and support large projects effectively.

A mid-sized consulting firm specializing in risk mitigation and project analytics for large-scale construction projects seeking to enhance data collection and analysis capabilities.

• Transition and modernize the existing application codebase within five months to support the client’s business goals.
• Reduce dependency on internal teams by implementing scalable, reliable architecture and cloud deployment.
• Enhance the application's performance by optimizing database models and scheduling algorithms.
• Secure the platform with advanced security features.
• Implement responsive design with mobile support to facilitate field data collection.
• Convert the application into a multi-tenant SaaS model deployed in the cloud to support scalability and multiple clients.

• Automated data capturing functionalities integrated with field tools and web interfaces.
• Risk analysis modules that identify early warning signals from collected metrics.
• Security mechanisms including user authentication, role-based access control, and data encryption.
• Responsive design supporting mobile devices and field use scenarios.
• Conversion of existing code to modern development frameworks with improvements in system performance.
• Deployment in cloud infrastructure supporting SaaS with multi-tenancy capabilities.
• Web service architecture enabling integration with external data sources and enterprise systems.

• Field data collection tools via web or mobile apps
• Third-party analytics or risk assessment tools
• User authentication services (e.g., OAuth, SAML)

• Application should be deployed in cloud infrastructure supporting scalability and high availability
• Response times should support real-time or near real-time data analysis
• Security features must comply with industry standards, including data encryption, secure authentication, and authorization
• Support for mobile devices to facilitate on-site data entry
• System must efficiently handle large datasets with performance metrics available for analysis

The new cloud-based analytics platform is expected to support scalable data collection and risk identification processes, enabling the client to reduce project delays and cost overruns. It aims to cut implementation time to launch within five months, leading to faster service delivery, improved risk mitigation accuracy, and increased client onboarding through a secure, accessible SaaS solution.