FinOps Swarm

Enterprise project finances run across three legacy systems: a mainframe ERP holding committed and actual costs, IBM TM1 holding the budget via a SQL source database, and Cognos BI as the reporting layer. When a change order is approved, all three systems should update. They rarely do. Nobody finds out until Cognos renders a report days later, by which time decisions have already been made on wrong numbers. This is not a data quality problem. It is an event propagation problem. Change orders fall into a manual queue that nobody owns end-to-end. A senior analyst spends 2-4 hours per project per week just to answer one question: what did we actually spend this week? Because the mainframe only stores cumulative running totals, not period-bounded figures. FinOps Swarm replaces manual reconciliation with six Band-coordinated AI agents. Agent 1 detects approved change orders and posts to the Band shared room. Agents 2 and 3 run in parallel: one checks the mainframe ERP, one checks the SQL source feeding TM1 via TurboIntegrator. Agent 4 waits for both findings in the Band room, then calls a local Llama 3.2 model on AMD hardware to generate a CFO-ready narrative. Financial data never leaves the network. Agent 5 surfaces only genuine exceptions to the CFO with a one-click decision card. Agent 6 computes period-bounded weekly spend automatically from mainframe snapshots. Band's shared room is load-bearing, not decorative. Agents 2 and 3 post independent findings. Agent 4 waits for both. Agent 5 reads everything. Built by a systems engineer who works on TM1 and mainframe pipelines daily. Every pain point is real.