Never overstock. Never run out. Always profitable.
Our AI models forecast demand with 95%+ accuracy, optimize reorder points across thousands of SKUs, and automate purchase recommendations — so your working capital works smarter, not harder.
Quantifiable Supply Chain Gains
Our predictive models deliver hard savings across carrying costs, waste reduction, and lost sales prevention — measurable from the first quarter of deployment.
AI-Powered Inventory Intelligence Platform
From demand sensing to automated replenishment, our comprehensive platform turns inventory from a cost center into a strategic competitive advantage.
Multi-Horizon Demand Forecasting
ML models trained on your sales history, seasonality, promotions, and external factors predict demand at SKU-location level.
- Short-term (7-day) & long-term (52-week) forecasts
- Promotion lift modeling built-in
- Automated new product introduction forecasting
Intelligent Replenishment Engine
Purchase orders generated automatically when stock hits predicted reorder points — accounting for every constraint.
- Supplier lead time & MOQ aware
- Dynamic safety stock calculation
- Multi-supplier optimization
Dead Stock Prevention System
Identify slowing items 60-90 days before they become dead stock. AI recommends actions to recover maximum value.
- Velocity trend detection
- Markdown & bundle recommendations
- Inter-warehouse transfer suggestions
Multi-Warehouse Network Optimization
Balance inventory across your entire distribution network to maximize availability while minimizing logistics costs.
- Regional demand pattern recognition
- Automated stock rebalancing
- Shipping cost vs. stockout trade-off analysis
Supplier Performance Intelligence
Track and predict supplier behavior to proactively adjust safety stock and reorder strategies.
- Lead time variance tracking
- Fill rate & quality scoring
- Risk-adjusted safety stock levels
Real-Time Analytics Command Center
Live dashboards with drill-down from category to SKU. AI-generated alerts before problems impact customers.
- Days-of-inventory remaining by SKU
- Anomaly detection & alerts
- Custom report builder & exports
See Your Inventory Future, Today
Our forecasting engine visualizes demand patterns, seasonality, and anomalies — giving your team complete confidence in every replenishment decision.
Beyond Basic Forecasting
Our models don't just extrapolate trends — they understand causality. Promotions, competitor actions, weather patterns, and macroeconomic indicators are all factored into every prediction.
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95.4% accuracy at SKU-week level across our client base — verified through 12-month back-testing.
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Continuous learning: Models retrain weekly on new sales data, adapting to shifting demand patterns automatically.
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What-if scenarios: Simulate the impact of promotions, supplier delays, or demand shocks before committing to purchase orders.
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Anomaly detection: Get alerted when actual demand deviates from forecast by more than 2 standard deviations — early warning for supply chain disruptions.
From Raw Data to Automated Replenishment
A proven, low-disruption implementation methodology that connects your systems, trains AI on your unique data patterns, and goes live in weeks — not months.
Data Integration & Cleansing
We connect to your ERP, POS, WMS, and supplier portals. Historical sales, inventory movements, and purchase orders are cleansed and unified into a single source of truth.
Model Training & Tuning
Custom ML models trained on your product lifecycle patterns, promotion calendars, seasonality curves, and supplier lead time variability. No black boxes — you understand what drives each prediction.
Back-Testing & Validation
We simulate forecasts against 12-24 months of held-out historical data. Models must achieve 90%+ accuracy before any automation is enabled. You review and approve the results.
Deploy, Monitor & Continuously Improve
Replenishment recommendations flow to your purchasing team or directly to suppliers via API. Models retrain automatically on new data — accuracy improves every week.
Predictive Inventory Across Every Sector
Every industry has unique inventory challenges. Our models adapt to your demand patterns, product characteristics, and supply chain constraints — delivering results from day one.
E-Commerce & DTC Brands
Forecast demand across 50,000+ SKUs, automate POs, and prevent stockouts during Prime Day, Black Friday, and flash sales. One client reduced lost sales by $4.2M annually.
Manufacturing & CPG
Optimize raw material and component inventory across global production sites. Align procurement with MRP schedules and reduce line-down incidents by 78%.
Healthcare & Pharmaceuticals
Maintain critical medication and supply levels across hospital networks. Expiry-date-aware forecasting reduces waste on perishable inventory by 40%.
Retail & Omnichannel
Balance inventory across 200+ stores and 3 DCs. Predict demand by location, automate inter-store transfers, and increase full-price sell-through by 22%.
Food & Beverage Distribution
Manage perishable goods with shelf-life-aware forecasting. Reduce spoilage by 35% while ensuring high-demand items are always available for restaurant and grocery clients.
3PL & Logistics Providers
Offer predictive inventory insights as a value-added service to your warehouse clients. Help tenants reduce their inventory costs while increasing your sticky revenue per account.
Everything You Need to Know
Common questions from operations, finance, and supply chain teams evaluating AI-powered inventory management.
How long does implementation take?
Most clients go live with initial forecasts within 4-6 weeks. Full automation of purchase orders typically follows 2-4 weeks after forecast validation. Enterprise deployments with multiple ERP integrations may take 8-12 weeks.
What data do you need to get started?
We need 12-24 months of historical sales/consumption data at the SKU-location level, inventory snapshots, purchase order history, and supplier lead time data. Our team handles all data extraction and cleansing.
Which ERP systems do you integrate with?
We have native connectors for SAP, Oracle NetSuite, Microsoft Dynamics 365, Acumatica, and Epicor. Custom integrations are available for legacy systems via REST API, EDI, or flat-file exchange.
How do you handle new products with no history?
Our models use attribute-based forecasting for new SKUs — mapping to similar products based on category, price point, seasonality profile, and supplier. Accuracy improves rapidly as the first 4-6 weeks of sales data comes in.
Can we keep human approval in the loop?
Absolutely. You can configure approval thresholds by dollar amount, supplier, or SKU category. Many clients start with human approval on all POs and gradually automate as confidence builds.
What's the typical ROI timeline?
Most clients see full payback within 60-90 days. The quickest returns come from dead stock liquidation and reduced stockouts. Inventory reduction savings compound over the first 6-12 months as safety stock levels optimize.
ML Infrastructure Built for Supply Chain
We combine time-series forecasting, probabilistic models, and real-time data pipelines — all running on enterprise-grade cloud infrastructure with 99.99% uptime.
Let AI Predict Your Next Order — With Precision
Tell us about your current inventory challenges — stockouts, overstock, manual reordering, or dead stock — and we'll build a predictive model tailored to your supply chain. First forecast delivered in 2 weeks, no commitment required.
