Apparel
Solvoyo’s AI-native platform unifies financial planning, buy planning, allocation, replenishment, and markdowns — helping retailers cut markdowns and get the right product to the right place at the right time.
5-10%
Sell-Through Improvement
5-10x
Faster Decisions
Don’t take our word for it
“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 digitize our pre-season planning processes, reduce manual work, create corporate memory, bring automation to buy planning and size optimization decisions.”
Your Supply Chain, Performing at Its Peak
10-15%
Markdown Rate Reduction
200-300 bps
Gross Margin Improvement
5-10x
Faster Decisions
95%+
No-touch planning
Solvoyo Platform
Built for Every Stage of the Lifecycle
AI-Powered Scenario Planning
AI-generated forecast seeds the MFP/WSSI collaboration platform, enabling faster alignment on category mix and inventory productivity without the back-and-forth of manual planning cycles.
Attribute-Based Buy Planning
Buy quantities are calculated using product attributes and store-specific placement rather than chain-average rates of sale — so new-season forecasts are sharpened by learnings from similar items, not distorted by blended averages that hide store-level demand variation.
Size Profile Precision
Size curves are recommended per store cluster and channel based on how comparable items actually sold, replacing one-size-fits-all averages with store-type-specific allocation that reduces size imbalances and improves full-price sell-through.
In-Season Decision Agility
Allocation decisions are automated at the moment of receipt using live sell-through signals — directing inventory to where demand is materializing rather than locking into pre-season plans that no longer reflect reality. Repeat-buy decisions for never-out-of-stock and core fashion items are automated based on size-level sales forecasts, lead times, minimum order quantities, exit dates, and budget constraints — eliminating manual tracking and reducing the risk of over- or under-commitment.
Margin Optimization
AI models optimize markdown timing and depth at the SKU or color-option level, protecting gross margin while maximizing end-of-season sell-through — without relying on blanket discount rules that leave money on the table.
Solvi – From Insights to Actions
Solvi, Solvoyo’s AI planning agent, acts as an always-on analytical partner for apparel planners — continuously monitoring sell-through trajectories, size availability, and inventory positions across every store cluster, flagging repeat buy opportunities before the selling window closes, surfacing transfer and markdown recommendations before margin is lost, and delivering prioritized action items that turn hours of manual WSSI analysis into decisions made in minutes.
Planning on Autopilot
Solvoyo runs the high-volume, repeatable decisions — what to send, what to chase, what to move, what to mark down — so your merchants and planners spend their hours on assortment, newness, and trend instead of manual rework.
One Plan, Every Channel
Stores and e-commerce, pre-season and in-season, finance and the floor all work from a single connected plan — replacing emailed spreadsheets and clashing versions with one set of numbers every team can act on.
Read the Floor, React in Time
Fashion rewards speed. Solvoyo turns live demand into a clear next move — double down on a breakout, ease off a slow style, rebalance between locations — while the selling window is still open.
Proven by Leading Brands
Apparel retailers across fast fashion, lifestyle, and concept retail already run on Solvoyo, reaching high recommendation-acceptance rates and measurable inventory and margin gains — on a platform configured to how they merchandise.
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.
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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.