Producing the P&L is rarely the hard part. The real work starts after the numbers come out, when analysts go line by line adding context, exporting commentary into spreadsheets, and trying to synthesize a coherent story across dozens of locations and files that are all moving on their own timelines. This is a pattern we're seeing across multiple customers, and it's exactly what we're building to solve. At #Workflow26, we hosted a session on "Building an AI Application for Finance using Sigma." Our team walked through how to rethink that entire process by turning the P&L into an app inside Sigma, where financial modeling, variance commentary, and AI-driven analysis all live in the same governed system. This recap by Kyle Herold covers how to eliminate version drift and manual aggregation risk, how Sigma Agents can categorize variance drivers and surface recurring patterns across periods, and what it looks like when finance moves from answering "what happened" to driving the "so what" and "now what." Check it out: https://lnkd.in/g5s3sX3P
