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
Measured outcomes
+7%
Margin uplift · first end-of-season cycle
Days
Markdown decisions executed (was weeks)
100%
Audit trail on every action — who, what, when
What's wired up
Systems connected
Merchandising system
Pricing & assortment
Warehouse (WMS)
Inter-store transfers
Store-facing tools
Tags & shelf-labels
Before · After
Before
Playbook on paper, scattered execution
Five banners, 50+ stores, a clear markdown playbook — and nobody actually following it consistently. Slow-moving stock was marked down too late, too uniformly, and the margin impact was significant.
After
Agents draft, humans approve
Each agent runs on its own cadence, builds a full proposal (rule followed, data used, expected impact) and routes it for approval at the team's existing thresholds. Approved actions execute directly — no re-keying into a workflow tool.
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, all formalised inside the intelligence layer — 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
Related: pair this with continuous replenishment to close the loop upstream, or see how the same orchestration layer handles execution across systems without re-keying.
More use cases
A seasonal buy plan, signed off in one review
A 14-store apparel buyer had to cut next season's open-to-buy by 12% — and built a sharper plan on two years of live sell-through instead of intuition.
Move stock before markdown is the only option left
A 9-store streetwear brand turned twice-a-season panic transfers into a calm weekly lever — moving stock six weeks before markdown was the only answer left.
Allocation that finally knows the network
A 14-store apparel network still split each season with a rule written when it had 8 stores. Solya re-allocated on what every store had actually become.
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