The client struggled with an outdated, manual Reverse Invoicing process that slowed operations and increased the risk of errors. Business users had to manually validate the Bay Area RI Program File before creating the final TCI file. The Trio application’s slow performance required a dynamic timeout and retry mechanism while the existing script for downloading Snowflake data was inefficient and slowed down processing. Handling large datasets in Excel created performance bottlenecks and delays. Ad hoc business requests for specific time-period reports further complicated the process. The AI-driven automation solution by Accelirate addressed these core issues:
A status dropdown was introduced in the RI Program File, allowing businesses to indicate when records needed re-validation or were ready for TCI creation. The AI Agent performed actions based on the status update.
The script for downloading data from Snowflake was removed, and instead, a direct connection to the Snowflake database was established, speeding up data retrieval. Eliminated unnecessary scripts by integrating directly with Snowflake Database significantly made the process faster.
Given the large and complex data, Excel was used as a database for faster updates, reducing file processing time and optimizing performance.
Deployed AI Agents for validation and error handling, ensuring data accuracy before TCI file generation. After validating the data, the AI Agent automatically generated reports and emailed notifications, ensuring smooth communication between the business users and the automation system with status updates on processing success and failure.
The unique aspect of the solution was the seamless integration of AI Agents into the client’s workflow, enabling intelligent automation without overhauling the existing system. AI Agents replaced manual business validation, providing an intelligent, adaptive decision-making system. The integration allowed for the automation of complex data validation tasks, the reduction of manual intervention, and a direct connection to Snowflake for faster data retrieval. The AI Agents’ ability to handle exceptions and manage large datasets with ease was pivotal in delivering significant time savings and increased accuracy in invoicing. Designed a scalable, business-controlled automation model, allowing users to dictate processing actions through a status dropdown. This end-to-end automation handled exception processing, reducing errors to near zero.