Solvoyo & AWS Retail Software Partnership
Solvoyo is now a part of the AWS Partner Network. Together, Solvoyo and AWS empower clients in their digital transformation journey.

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in the cloud.
Solvoyo has joined forces with AWS, one of the world’s most comprehensive and broadly adopted cloud platform, to deliver a seamless and scalable experience for businesses of all sizes. With Solvoyo’s expertise in supply chain planning and optimization and AWS’s unparalleled cloud infrastructure, we provide cutting-edge solutions to optimize your business performance and increase long-term profitability. Our collaboration enables us to leverage advanced technologies such as Machine Learning, Artificial intelligence, and data analytics to help companies make informed decisions with multiple capabilities that incorporate descriptive, diagnostic, predictive, and prescriptive analytics that drive their supply chain success.
Don’t take our word for it
“Solvoyo gave us a single source of truth across planning. We cut inventory by 30% while improving service levels.”
“The autonomous planning engine paid for itself in months. Our planners now focus on decisions, not spreadsheets.”
“Forecast accuracy jumped double digits in the first quarter. Solvoyo is a true partner, not just a vendor.”
“Implementation was faster than anything we had seen. We were live in one region within weeks, not quarters.”
“From demand to replenishment, everything finally talks to each other. The visibility across our network is a game changer.”

Case study
Vestel Orchestrates Omnichannel Excellence Building a Living S&OP Ecosystem with Solvoyo
Vestel – Consumer Electronics ManufacturerVestel, a global leader in consumer electronics and appliances, launched the Autonomous Retail Project (OPP)

Case study
Demand-Driven Replenishment & Last Mile Delivery
g2m, a leading foodservice distribution company in Turkey,increased collaboration and planning productivity while realizing $8.7M annual savings by in

Case study
Smarter S&OP
Duzey – Wholesale FMCG Distributor Demand driven replenishment planning with sales forecast collaboration and automated safety stock calculation
Start your journey now
Begin the comprehensive digital transformation of your business with Solvoyo’s end-to-end intelligent platform.
Frequently Asked Questions
Apparel planning is defined by long lead times, size-color complexity, unforgiving seasonality, and the pressure to commit to inventory months before demand is clear. Getting the wrong size mix, missing a trend, or allocating to the wrong stores compounds into end-of-season markdown exposure that erodes margin across the entire range.
An AI-powered, end-to-end planning platform that integrates and automates apparel planning decisions from pre-season buy through in-season management, across fashion, seasonal, and basic product categories.
Markdown exposure is reduced at every stage — through localized initial allocations that land the right sizes at the right stores from day one, in-season transfers that redirect slow-moving inventory before the selling window closes, and AI-driven markdown optimization that times and sizes discounts at the SKU level to maximize full-price sell-through.
Most apparel customers turn planning into a competitive advantage in 12–16 weeks, with measurable results in 3–4 months.
Yes. The same platform plans short-lifecycle fashion, seasonal ranges, and continuity basics, applying the right method to each.
Solvoyo customers reach 95%+ automation on daily operational planning decisions including initial allocation, store replenishment, transfers, and markdown optimization, freeing planners to manage exceptions and strategy.
Apparel retailers using Solvoyo have achieved significant improvements in full-price sell-through, inventory turns, and markdown reduction — with planning cycles compressed from days to hours and AI recommendation acceptance rates exceeding 90%. Customers report measurable working capital improvements within the first season, driven by more accurate initial allocations and faster in-season response to demand signals.









