AI Native Supply Chain
Platform
Enabling Smarter, Faster and Transparent Decisions at Scale
AI Native Supply Chain
The Adaptive, Decision Layer for Supply Chains
Our AI-powered applications and workflow assistants plan, decide, act, and learn alongside your team
Demand Forecasting
Improve forecast accuracy by 1,000+ basis points with AI-powered probabilistic forecasting
Our forecasting engine generates probabilistic forecasts that capture full demand distributions across SKUs, channels, and time horizons. Strum maintains a library of forecasting models from classical statistical approaches to machine learning and deep learning architectures, automatically selecting the best model for your needs. Simulate complex decision scenarios across multiple demand, inventory and supply inputs instantly
Three Core Pillars of Intelligence
1
Rapid Data Integration
Escape the cost and fragility of custom integrations. Onboard data in days not months using our canonical supply-chain schema with LLM-powered semantic understanding across demand, supply, inventory, product hierarchies and relevant entities. Integrates once, and evolves with your business
2
Adaptive Application Layer
Industry-specific model libraries with curated forecasting and optimization engines. Strum automatically selects the best model, combining traditional statistical methods with advanced machine learning and deep learning models. This is configurability by design without costly customization
3
Inference and Actions Layer
A single interface that guides teams to the most critical actions first. Simulate complex scenarios across applications and run cross-functional workflows. Use our Agents to get real work done through applications while your team focuses on inputs, judgement and orchestration.
Measurable Business Impact
Strum AI delivers tangible results that drive top-line growth and bottom-line profitability
0.5% - 2%
Annual Revenue Growth
Through improved forecast accuracy, demand elasticity models, price/promotional modeling, and advanced seasonality/trend prediction
20-75 bps
Operating Margin Improvement
Via stochastic inventory optimization, decision latency reduction, and rapid scenario modeling
35-50%
Reduction in Excess Inventory
Lower excess and obsolete inventory costs through intelligent optimization
95%+
On-Time & In-Full Shipment Rates
Achieved through channel data integration, out-of-stock correction, and AI-powered fulfillment and allocation
50%+
Cycle Time Reduction
In key cross-functional workflows through AI assistants, on-demand data ingestion, and simulation