Moving on to the invoicing process, we implemented an automation feature that checks provider invoices against historical data for similar jobs. This helps verify if the pricing, materials, and resources used are consistent with past records. If the system detects any discrepancies, it flags them for the OC to review. This automation reduces the workload on OCs, allowing them to focus on more critical tasks, and speeds up the overall process.

Initially, we had a more ambitious plan to integrate a bot that could assist OCs in filling out forms and identifying errors in real-time—something akin to what ChatGPT does today, but this was before such technology was widely available. Due to time and technical constraints, we had to scale back this idea. However, we didn’t abandon it entirely. We incorporated a feedback system that still helps OCs catch potential errors, ensuring accuracy without the full AI integration we originally envisioned.

These were the main features that guided our high-fidelity designs. Each decision was made with the user experience in mind, aiming to create a platform that is not only functional but also intuitive and efficient for the users who rely on it daily.