We built the tool we kept wishing existed
Stockvyne was founded in Atlanta in 2023 by retail operations veterans who spent years watching well-run brands make avoidable inventory mistakes — not from bad judgment, but from the wrong data arriving too late.
Give growing omnichannel brands the forecasting and allocation infrastructure that used to require a full analytics team
Enterprise retailers have had SKU-level demand sensing and DC-to-store allocation systems for decades. They run 20-person supply chain teams, six-figure ERP implementations, and dedicated data science functions. The outputs are good — but the infrastructure is completely inaccessible to a brand doing $5M across three channels.
Brands in the $2M–$20M range run on Shopify exports, shared Google Sheets, and whatever sell-through report their wholesale platform generates. The gap between those two worlds is enormous — and it explains why mid-market brands routinely carry 20–30% excess stock on slow movers while stocking out on their A-velocity SKUs every peak season.
Stockvyne is not a watered-down version of a Blue Yonder or o9 implementation. It's a product designed from scratch for the 50–500 SKU omnichannel brand — where the planning team is two or three people, the catalog changes seasonally, and the data lives in five different systems that have never talked to each other.
Who we are
Claire Fontaine
CEO & Co-FounderPreviously led demand planning at a multi-brand DTC and wholesale operator managing 200+ active SKUs across three channels. Built the spreadsheet models, hit their limits, and spent two years figuring out what a proper tool would look like. Co-founded Stockvyne in 2023.
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Marcus Osei
CTO & Co-Founder10 years building supply chain data pipelines — at an omnichannel retailer managing thousands of SKUs, then at a logistics tech company. Joined Stockvyne as CTO to build the forecasting infrastructure that growing brands actually need: fast to connect, built per-SKU, and honest about what it doesn't know.
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Priya Anand
Head of Customer SuccessSpent six years as a retail operations consultant, onboarding mid-market brands onto inventory and ERP systems. Knows exactly where the handoff between software and real planning behavior breaks down — and joins every new Stockvyne customer's onboarding call herself for the first 90 days.
LinkedInThe problem Claire had been solving manually since 2017
In late 2022, Claire was leading demand planning at a DTC and wholesale brand with 200+ active SKUs. She'd spent five years building progressively more sophisticated spreadsheet models — adding columns, linking tabs, pulling from Shopify exports and Faire reports and manually entered DC stock counts. The models worked, more or less. But every Friday before a peak weekend, she'd catch herself making a judgment call on which stores to ship to based on a snapshot that was 48 hours old.
She called Marcus in late 2022. They spent four months talking to other planning leads at similar brands. The pattern was the same everywhere: good operators making preventable mistakes because the data took too long to arrive and there was no system connecting DC stock to store velocity to the week's demand forecast.
The first Stockvyne prototype ran in January 2023. The first paying beta customer — a home goods brand running DTC and Faire wholesale — signed in March 2023. Stockvyne launched publicly in October 2023. The company is headquartered in Atlanta, GA.
Three principles that shape every product decision
Show the reasoning, not just the answer
Every DC-to-store transfer recommendation comes with the forecast that generated it, the current weeks-of-stock at both locations, and the urgency window. A planning team that can't explain a decision to their VP won't use it twice. We build for that reality.
Features come from operators, not roadmaps
The allocation engine, the dead stock aging report, the open-to-buy awareness in replenishment — each came directly from a planning lead telling us what was breaking in their workflow. We don't ship features that sound impressive in a demo but fail in daily use.
First forecast within 48 hours of connecting
We've obsessed over integration time, historical import speed, and onboarding friction because we know the cost: every week a brand runs without accurate SKU-level forecasts is another week of allocation decisions made on a spreadsheet. That's not acceptable to us.
A small team building something specific
We're not trying to be the inventory platform for everyone. We serve omnichannel brands with 50–500 active SKUs, and we intend to be the best option for that segment. If that's where you operate, we'd like to hear from you.