Arahi AI forecasts stock. Vendlore closes the loop and reports per-channel profit.
Arahi AI's strength is AI-driven SKU demand forecasting and supplier replenishment suggestions. Vendlore keeps that forecasting power AND joins it with supplier lead times, ad-spend attribution, and a weekly per-channel contribution-margin report — the one Arahi does not send. ROAS dashboards watch ad spend. Vendlore watches the three signals together.
- Compared with
- Arahi AI
- Decision cadence
- Continuous
- Weekly report
- Per-channel contribution margin
SKU levels reconciled across every storefront and warehouse continuously.
Live per-supplier ETA commands the reorder math against the actual lead time.
Spend stitched to the order that produced it; carried into the per-channel margin report.
Vendlore vs Arahi AI — feature by feature
The same shape every comparison page uses. Cells tagged with a[CLAIM]marker refer to the competitor-features in this brief's source mapping; validate them and replace the text without changing this page shell.
| Capability | Vendlore | Arahi AI |
|---|---|---|
| Decision model | [CLAIM] SKU levels + supplier lead time + ad spend joined in one continuous loop. | [CLAIM] SKU forecast + ad spend surfaced as separate reports on different cadences. |
| Weekly per-channel profit report | [CLAIM] Every Monday: revenue minus COGS/shipping/fees/fulfillment/attributed ad spend, per channel, ranked by margin %. | [CLAIM] Forecast accuracy and inventory health; per-channel contribution-margin P&L is not the standard report. |
| SKU-level state model | [CLAIM] Reads every connected storefront + warehouse continuously; reconciles in-transit and committed-but-unreceived automatically. | [CLAIM] Produces SKU-level forecasts per location; the underlying state must be synced in separately. |
| Supplier lead time | [CLAIM] Live ETA profile per supplier refreshed from carrier, ASN, historical variance — drives reorder math. | [CLAIM] Optimizes reorder timing against forecast; no first-party live ETA signal. |
| Ad spend attribution | [CLAIM] Spend stitched to the order that produced it; result carried downstream to the per-channel margin report. | [CLAIM] No native ad-platform integration as a first-party signal. |
| Closed-loop learning | [CLAIM] Every shipped PO, every shipment outcome, every weekly margin delta feeds back into the next decision. | [CLAIM] Forecast cycle delivers a prediction; the executed outcome does not close the loop on the next forecast. |
| Reorder execution | [CLAIM] POs delivered through email/Slack/EDI/PIM or queued for human approval — closed-loop by default. | [CLAIM] Surfaces a reorder suggestion; execution lands in a separate workflow tool. |
Three signals in one decision, not three reports side-by-side.
Arahi AI typically delivers its SKU forecast on one cadence and surfaces ad spend on another. Vendlore joins inventory, supplier ETA, and attributed ad spend into one decision model and reconciles them continuously — so a daily ad-spend spike that would have looked healthy in isolation is correctly flagged as net-negative once COGS and the supplier's actual lead time are pulled in.
Contribution margin per storefront, not ROAS per campaign.
ROAS answers "did this campaign produce revenue?" — it doesn't answer "did this storefront make money this week?" Vendlore ships the latter every Monday: revenue minus COGS, shipping, fees, fulfillment, and attributed ad spend, per storefront and per ad channel, ranked so the channel that earns the most per dollar sits at the top and the channel that bleeds sits at the bottom. Arahi's standard reporting focuses on demand forecast accuracy and inventory health — the per-channel P&L is not its primary output.
Reorder math against the supplier's actual lead time.
Each supplier carries its own ETA profile in Vendlore — refreshed against live carrier updates, ASN arrivals, and historical variance. Reorder math runs against the actual lead time, not the one printed on the supplier sheet six months ago. Arahi AI optimizes reorder timing against its forecasted demand curve; when that lead time drifts, Arahi has no first-party signal to correct the assumption.
A continuous loop, not a nightly export.
Vendlore runs Watch → Decide → Route → Learn on independent cadences and closes the loop every day. Every shipped PO, every shipment outcome, and every weekly margin delta feeds back into the next decision. Arahi's deliverable is a forecast — Vendlore's deliverable is the executed reorder decision tied to its outcome, end to end.
Start watching the three signals — and the channel they make money on.
Open Vendlore's weekly per-channel contribution-margin preview to see revenue minus COGS, shipping, fees, fulfillment, and attributed ad spend — ranked so the channel that earns the most per dollar sits at the top.