AI systems for consumer products.
The workflow pattern we see in this industry, and what we would build for it.
01
Promo window opens
A retailer asks for the promotion plan. The planner mines last year's spreadsheets for what ran.
02
Plan negotiated
Depth and timing are set from precedent and gut feel. The ROI case is asserted, not modeled.
03
Forecast adjusted by hand
Demand plans are overridden in meetings. SKU-level error flows straight into inventory and waste.
04
Deductions reconciled late
Months later, trade spend is reconciled against deductions by hand. Leakage is found after it is gone.
A trade planning agent.
An agent that drafts promotion plans from measured past lift, updates the demand forecast daily from POS and inventory signals, and flags deductions worth disputing with the evidence attached. Your commercial team keeps the final say on every plan. The agent removes the spreadsheet archaeology.
10 to 14 weeks from kickoff to a live production system. We stay through adoption.
Eval harness
Checks agent outputs against a test set before release.
Reliability gates
Hard checks the system must pass before it ships.
Live production system
The working system in your stack, not a report.
Adoption Mile
To the 70 percent weekly-active bar by day 90.
Trade promotions that break even or better
Under 30 percent
IllustrativeSKU-level forecast error, common baseline
30 percent or more
IllustrativeTrade ROI improvement from measured planning
Varies by category
Illustrative
Ranges are industry observations for orientation. They are not ClearForge results. Our results live on the proof page.
See the proofStart where every engagement starts. The fixed-fee Diagnostic maps this workflow in your commercial team in 2 weeks.
Starting point · Forge Diagnostic