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LIVE CONVERSATION
Intelligence, not just answers
app.replenify.io
app.replenify.io
R
Reppi
Online
Which stores should I move NK-AF1-BLK stock to this week?
Based on current sell-through velocity, I recommend moving NK-AF1-BLK to these 3 stores:
1. Sandton City — 3.2x velocity, 0 units
2. V&A Waterfront — 2.8x velocity, 1 unit
3. Gateway — 2.1x velocity, 2 units
Estimated GP impact: R8,340. Want me to generate the move orders?
Why not Menlyn Mall?
Menlyn already has 8 units with 3.4 weeks of cover. Moving more would exceed the size-run ceiling. Replenify blocked it with reason code SUFFICIENT_COVER.
Why is Store 14 underperforming in sneakers this month?
Store 14 (Menlyn) sneaker sell-through dropped 34% vs last month. Three factors:
1. Broken size runs in 3 of 5 top SKUs
2. Size 42-43 stockout since week 2
3. Competitor opened 200m away on Mar 3
Rebalancing engine has 12 pending moves to fix the size gaps. Want me to show them?
Ask Reppi anything...
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CAPABILITIES
Works across every module
Reppi is not a chatbot bolted onto a dashboard. It is the conversational interface to Replenify's auditable engine — with access to every module, every store, and every SKU in your network.
1
Ask in plain English, get data-backed answers
No query language. No dashboards to navigate. Ask Reppi a question about any store, SKU, or category and get a specific, data-grounded response.
2
Cross-module intelligence
Reppi sees patterns across rebalancing, allocation, and pricing. It connects sell-through velocity to markdown risk to replenishment timing — the full merchandise lifecycle in one conversation.
3
Store-specific analysis
"Why is Store 14 underperforming in sneakers?" Reppi drills into store-level data — sell-through rates, size curve mismatches, broken ranges, weeks of cover — and gives you an actionable answer.
4
Anomaly detection
Reppi flags issues before they become problems. Unusual sell-through drops, emerging stockout patterns, size curve shifts — surfaced proactively, not discovered at markdown season.
5
Explainable recommendations
Every answer includes the reasoning chain. Ask "why" and get a traceable answer grounded in your actual data — not a statistical black box.
6
Report generation on demand
Category reviews, store performance summaries, rebalancing impact analysis. Ask Reppi and get structured output ready for your Monday morning meeting.
NOT GENERIC AI
How Reppi is different from generic AI
General-purpose AI tools generate plausible text. Reppi generates verified answers from your actual inventory data.
Every answer traces back to your data
Every answer is grounded in your actual inventory data. Reppi queries the auditable engine, not a general-purpose language model. If the data does not support an answer, Reppi says so.
Reppi explains its reasoning
Ask "why" and get a traceable answer. Every recommendation links back to specific data points — sell-through velocity, weeks of cover, size run completeness, freight cost calculations.
Reppi learns your business
It knows your stores, your categories, your seasons. Store 14 is not a generic node — it is your Sandton City flagship with specific demand patterns, customer demographics, and performance history.