Toolio is the AI-powered merchandise planning platform built to scale with retailers. From fast-growing DTC brands to complex, multi-brand enterprise operations — across apparel, footwear, accessories, retail, and health & beauty.
AI forecasting runs across every module: merchandise financial planning, assortment, allocation, and replenishment, predicting demand down to the SKU-location level, so growing teams get enterprise-grade planning power without an enterprise-length rollout.
Customers see a 2-3% margin improvement, a 5-10% increase in in-stock rate, and a 35% reduction in planning time, for a 10x return on investment.
Key Benefits
→ AI forecasting built into every module, powering growth at scale. The same forecasting engine drives merchandise financial planning, assortment, allocation, and replenishment, predicting SKU x location-level demand and incorporating new launches, promotions, and seasonality as the business expands.
→ Enterprise-grade, built to scale with you: dynamic hierarchies, custom metrics, and multi-channel aggregation mean Toolio supports a single brand today and multi-brand, multi-channel enterprise complexity tomorrow, without a re-platform.
→ 10x ROI, powered by 35% faster planning cycles. Teams move from spreadsheet cycles to one live plan, freeing up time to open new channels, launch new categories, and scale faster.
→ 5-10% higher in-stock rate. AI-driven store-level demand forecasting and automated transfer order recommendations put more inventory in front of demand, capturing sales as the business grows.
→ 2-3% margin improvement. AI-assisted assortment rationalization gives merchandising teams the confidence to expand into new categories and styles without diluting margin.
→ 100% cloud-based with no-code configuration — teams stand up new workflows, brands, and regions themselves as they expand, without waiting on a professional services engagement for every change.
→ Enterprise ERP integration, ready on day one. Native integrations with SAP, Oracle, Microsoft Dynamics, and other major systems mean Toolio becomes the merchandising and forecasting layer on top of whatever a growing or enterprise retailer already runs.
Merchandise Planning
As the business scales, AI-driven actuals and forecasts flow in automatically from your commerce stack, so the plan grows with you instead of requiring more manual reconciliation at every new stage.
Planners build top-down, bottom-up, or middle-out and let Toolio's forecasting engine reconcile the difference, a structure that holds as complexity increases from single-brand to multi-brand and multi-region.
Every stakeholder gets their own view, sliced by whatever metrics and attributes matter to their role, and re-cuts a roll-up by channel, category, or brand on the fly as the org chart grows.
Assortment Planning
This is where the 2-3% margin improvement compounds as you scale: AI-generated depth-and-width recommendations give merchandising teams the confidence to expand into new categories, styles, and channels without diluting margin.
Line planning starts from AI-generated, cluster-appropriate placeholders instead of a blank page, so teams can launch new store clusters or markets faster.
Style development flows straight from PLM into the assortment plan, and the assortment can be reviewed visually, season over season.
Core Replenishment
The forecasting engine retrends automatically as new sales data comes in, so planners spend their time on strategic growth decisions instead of rebuilding projections from scratch every time the business adds SKUs or locations.
Promotions are factored into the AI demand forecast automatically from a centralized calendar, and replenishment recommendations scale with lead times and safety stock as the network expands.
Purchase Order Manager
Purchase orders generate directly from consolidated receipts, with minimum order quantities and freight already factored in and logic that holds whether you're managing one vendor or a global supply base.
Receipts are pulled forward automatically to hit vendor minimums, and planners see the AI-forecasted inventory impact of a PO before it's approved, supporting confident, faster decision-making as order volume grows.
Reporting
Teams see the full evolution of the assortment from pre-season to in-season, giving leadership the real-time visibility needed to scale confidently into new categories and markets.
Scenarios are compared side by side to model the financial upside of new growth bets before committing capital.
Allocation
The 5-10% in-stock rate improvement scales with the store network: AI and statistical forecasting predict SKU x location-level demand, accounting for new launches and promotions, so allocation keeps pace as new stores and channels come online.
Transfer orders generate automatically against safety stock targets and store capacity, and push directly into the ERP. Logic built to run at enterprise scale across hundreds of locations.
Store clusters build automatically from AI-driven product performance analysis, so the model adapts as the store fleet grows.
Average Rating: 4.8/5.0
Total Reviews: 10
How Do G2 Users Rate Toolio?
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Integrations: 9.2/10 (Category avg: 8.5/10)
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Product Display: 9.6/10 (Category avg: 8.8/10)
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Reports & Analytics: 9.6/10 (Category avg: 8.4/10)
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Has the product been a good partner in doing business?: 10.0/10 (Category avg: 9.2/10)
Who Is the Company Behind Toolio?
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Seller: Toolio
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Year Founded: 2019
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HQ Location: Brooklyn, US
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LinkedIn® Page: www.linkedin.com
83 employees on LinkedIn®
Who Uses This Product?
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Company Size: 60% Small, 40% Medium
What Do G2 Reviewers Say About Toolio?
AI-generated summary from verified user reviews
Pros
- Users appreciate the informative analytics of Toolio, which enhance decision-making for effective marketing strategies.
- Users value Toolio for its automation capabilities, streamlining critical workflows and providing real-time insights effectively.
- Users value the insights and dashboards in Toolio, enabling informed decision-making effectively.
- Users appreciate the ease of use of Toolio, finding it efficient for stock management and data integration.
Cons
- Users find the difficult learning curve initially challenging, but it ultimately provides valuable assistance once mastered.
