Transform your Category Management processes with AI-driven solutions
Seamlessly reconcile merchandise hierarchy targets with SKU-level assortment and buying decisions. Eliminate spreadsheet-driven version management and optimize item lifecycles with automated recommendations for repeat buys.
20-50%
20-50%Stock-out reduction
3-8x
3-8xPlanner productivity
Don’t take our word for it
“Using Solvoyo Assortment Planning has provided a huge convenience to us as we replaced our manual methods to achieve faster analysis and decision-making. We can easily see the reference products used in generating new purchase orders and review our buying decisions.”
“80% of IT tools investment fails if the partners don’t strive to continuously improve and adapt. That is what sets our partnership with Solvoyo apart.”
“Solvoyo has been a very effective solution partner in our fast growth and digital transformation journey. Using Solvoyo’s platform for fashion planning solutions, we were able to bring automation to buy planning and size optimization decisions.”
“When I write or speak about supply chain management, I always state that the purpose of a supply chain is to do one thing – enable growth. I believe Solvoyo is the optimal supply chain platform to help companies achieve the growth they desire.”
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Digital Transformation for Pre-Season Planning
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Solvoyo Platform
Your Supply Chain, Performing at Its Peak
20-50%
Stock-out reduction
3-8x
Planner productivity
18-23%
Stock cover reduction
95%+
Decision Automation on daily operational planning
Transform your Category Management processes with AI-driven solutions
Assortments That Match Local Demand
Localize collections by store, cluster, or region so every customer sees an assortment built for them, not a generic template.
Smarter Forecasts, Fewer Costly Mistakes
Machine learning models predict lifecycle sales, size-selling patterns, and first-time item performance, reducing markdowns and stockouts.
Less Manual Work, Faster Time to Market
Automated diagnostics, prepack recommendations, and ERP-integrated PO generation cut lead times and eliminate spreadsheet errors.
One Source of Truth Across Teams and Collections
Cloud-based workflow keeps planners, buyers, and regional managers aligned in real time, building a corporate memory that lasts.
Plan Once. Execute Everywhere. Always in Sync
Planning decisions flow into execution without manual re-entry — with real-time, bi-directional ERP and WMS integration that keeps every recommendation grounded in the current state of the supply chain.
Solvi — From Insights to Actions
Solvi, Solvoyo’s AI planning agent, continuously analyzes trading performance across categories, options, and store clusters — quantifying the margin and revenue impact of every recommended action so the most commercially consequential decisions get prioritized first, and no repeat-buy opportunity or markdown risk gets missed.
Solvoyo Differentiators
Autonomous Decision Making
Executes high-quality supply chain decisions with little to no planner intervention.
95%+ User Acceptance
Drives recommendations planners trust enough to accept and execute at scale.
Optimization + AI + Heuristics
Combines mathematical rigor and machine intelligence to outperform rule-based planning.
Real-World Constraint Modeling
Builds real-world operational constraints directly into every decision the system makes.
Network Wide Objective Solving
Optimizes cost, service, inventory, and feasibility across the full supply chain at once.
Unified Data and Execution
Connects data, planning, diagnostics, and action in one system built for execution.
Start your journey now
Begin the comprehensive digital transformation of your business with Solvoyo’s end-to-end intelligent platform.
Frequently Asked Questions
Category and assortment planning is the retail process of deciding which products to offer, in what quantities, and across which stores or channels for an upcoming season. It covers collection design, localized buying, size and prepack optimization, and the management of limited-time promotional products.
Assortment localization differentiates product offerings or timing across markets, store clusters, or regions to better match local customer demand. Solvoyo enables this through store clustering, store-level forecasting, and the ability to set different assortments, sizes, in-store dates, and depth targets by segment.
New products are forecast using attribute-based models that identify the most similar historic items, translated into store-level demand estimates for the new product based on category, price point, and product attributes. Similar item selection prioritizes recent history to reflect current demand trends. For fashion retailers, attribute-based forecasts feed directly into initial allocation — landing the right quantities and size ratios at the right clusters from day one. Product attributes digitalized at the development stage flow directly into the forecasting and buying workflow, eliminating manual re-entry between development and planning.
Size and prepack optimization determines the right size breakdown and prepack combinations for each store or region based on similar-item size-selling analysis. This reduces size imbalances, lowers inventory costs, and improves on-shelf availability for the sizes customers actually buy.
Solvoyo’s in-season management capabilities monitor every active item continuously against its sell-through trajectory — generating automated repeat-buy recommendations for items tracking ahead of plan and markdown recommendations for underperformers, sized against remaining selling life and exit dates. Solvi, Solvoyo’s AI planning agent, surfaces prioritized action items with quantified business impact so merchants act on the highest-consequence exceptions first rather than building their own analysis from a WSSI report.
Yes. Solvoyo offers real-time integration with ERP and PLM systems to automate purchase order generation, sync master data, and reconcile plans across systems, eliminating manual data entry and reducing errors.
Retailers using Solvoyo consistently report planning cycle compression from days to hours, AI recommendation acceptance rates exceeding 90%, and measurable business results within three to six months of go-live.