Schema is the first AI-native financial platform designed to answer strategic questions live, in the room, with zero compromise on granularity, rigor, or speed.
Legacy platforms impose three compromises that have nothing to do with the people and everything to do with the tools. We built Schema to eradicate them.
To answer quickly, you aggregate. You model at the summary level because the tool chokes on the details. The insight hides in the cohort, the contract, the rep level — the detail you threw away.
Run the full business model — every contract, every employee, every cohort — in real-time. No aggregation. No simplification. Millions of data points, milliseconds.
When strategy shifts in the meeting, you can't answer live. You retreat to your desk for three days of spreadsheet gymnastics. By the time you return, the decision has been made without you.
Answer the "what-if" instantly. Restructure territories, stress-test margins, model the P&L cascade — live, shoulder-to-shoulder with the business. Be the co-pilot, not the historian.
You know a simple growth rate is wrong. You want simulation, correlation analysis, driver decomposition. But that requires a data science ticket and a three-week wait. So you use simple math to solve complex problems.
Advanced simulation, correlation-aware forecasting, and driver decomposition are native to the platform. Drag a slider, run a thousand futures. No code. No tickets. No waiting.
AI reasons. The engine calculates. Both leave a trail. Every number traces back to its inputs, its formula, its assumptions.
Click any value and see exactly how it got there. Every cell, every driver, every assumption — one click to full lineage.
See what the AI did and why. Every decision, every recommendation, every scenario the agents surface is logged.
Most AI in finance summarizes text. Schema's AI does the math. It works inside the financial model — running scenarios, decomposing variance, surfacing risks, finding the optimal path — not in a sidebar drafting emails about what the slow platform eventually computed.
A chatbot sidebar on a legacy platform. It summarizes data you already have. It drafts narratives from numbers it didn't compute. The interface for toil changes. The toil doesn't.
Agents that run scenarios, decompose variance to the driver level, stress-test your plan against a thousand futures, and draft the board narrative from the decomposition. They work inside the model. Their reasoning is visible. You supervise and decide. They execute and explain.