Assumptions & governance
Automation has
a decision boundary.
The four models on this site show workflow mechanics, not product performance. A real implementation starts in shadow mode against a company's own historical outcomes, and earns autonomy one decision class at a time — not all at once, and never past this line.
Shared boundary: No live contract, payment, supplier communication, employee action, card hold, or system-of-record update happens anywhere on this site. All data is fictional. Every download these models generate is built locally in your browser.
Calibrate with confirmed outcomes
Replace the illustrative volumes, rates, costs, thresholds, and recovery assumptions in these models with your own observed data before treating any impact number as real.
Run in shadow mode
Compare the model's recommendations against licensed counsel, controllers, buyers, auditors, and policy owners — and against known case outcomes — before it changes anything in a live system.
Measure misses and harm, not just savings
Track precision, recall, false holds, false auto-posts, reviewer time, appeals, and reversals. A model that only reports what it caught is reporting half the picture.
Increase autonomy by action class
Let low-risk, reversible actions go first. Legal conclusions, cash movement, contractual commitments, fraud findings, and employee consequences stay explicitly authorized by a named person, always.
- Company data
- Fictional composite cases
- Software cost
- Not modeled
- External action
- None performed
- Combined ROI
- Intentionally not calculated