The Challenge
What FinBot Was Facing
FinBot had built powerful AI that processed financial data automatically — but the workflows surrounding it were still manual. Staff were hand-triggering AI processes, copying outputs between systems, and chasing exception approvals by email. The AI was doing its job; everything around it was not. Month-end close was still consuming three full business days despite the AI investment.
The Solution
What We Built
We mapped every manual touchpoint in the month-end workflow and built an automation layer that connected the AI engine to the surrounding systems: triggering analysis when data arrived, routing exceptions to reviewers with full context pre-populated, pushing approved outputs downstream, and generating client summary reports without human involvement. The whole pipeline was monitored in real time.
Results