AI systems for retail and e-commerce.
The workflow pattern we see in this industry, and what we would build for it.
01
Sales data lands
Weekly sell-through reports arrive as exports. Planners stitch them together in spreadsheets.
02
Demand read by hand
Forecasts are adjusted from experience. Store-level and SKU-level signals get averaged away.
03
Prices and markdowns set
Markdown depth and timing follow rules of thumb. Margin is negotiated cell by cell.
04
Changes keyed per system
Price and allocation changes are entered by hand across channels and stores. Errors surface on the shelf.
A pricing and markdown agent.
An agent that reads sell-through daily, drafts price and markdown recommendations with margin guardrails, and stages the changes for planner review. Merchants keep the final say on every price. The agent removes the spreadsheet assembly and the re-keying.
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.
Planner time on report assembly per week
8 to 12 hours
IllustrativeReturns share of online sales, many categories
About 30 percent
IllustrativeMargin lift from disciplined markdowns
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 merchandising office in 2 weeks.
Starting point · Forge Diagnostic