AI agents that don't just suggest — they do the work
A footwear group deployed Solya agents on markdown, transfers and reordering. Approvals stayed human; the busywork did not.
Outcome
+7% margin uplift
Network
5 banners · 50+ stores
The challenge
The merchandising team had a clear markdown playbook on paper, but executing it across five banners and 50+ stores meant nobody actually followed it consistently. Slow-moving stock was being marked down too late, too uniformly, and the margin impact was significant.
What we changed
Solya agents were given the team's markdown rules, transfer guardrails and reorder logic — and the keys to the systems that execute them. Each agent runs on its own cadence, drafts the decisions, and routes them for approval based on the team's existing thresholds.
How decisions get made
An agent doesn't just produce a recommendation list. It builds a full proposal with the rule it followed, the data it used and the expected impact. Reviewers approve, edit or reject — and the agent learns which adjustments are systematic vs. one-off.
Where it lands
Approved actions hit the merchandising system, the warehouse, and store-facing tools directly. Nothing gets re-keyed into a separate workflow tool — the agent's output IS the workflow.
What changed
- +7% margin uplift on the first end-of-season cycle
- Markdown decisions executed in days, not weeks
- Full audit trail on every action — who approved, what changed, what the agent saw