An intelligence-first foundation for operational agility
Helping manufacturers, logistics providers, and distributors build resilient, data-driven supply chains.
AI has become a transformative force in the supply chain industry, revolutionizing how companies forecast demand, manage inventory, optimize logistics, and respond to market disruptions. Today’s supply chains are expected to be agile, data-driven, and responsive—goals increasingly achievable through AI’s capabilities in automation, prediction, and decision support.
AIRe, powered by SUTRA, brings AI-native transformation to the supply chain—turning real-time data into foresight, coordination, and control. Designed to operate securely across fragmented ecosystems, it provides predictive, multilingual, and domain-aligned intelligence across the full supply chain lifecycle—from planning to fulfillment.
Move beyond dashboards and rule-based systems. Achieve synchronized operations with decision-grade AI that continuously learns and adapts.
How AI is Being Applied in Modern Supply Chains
Predictive Forecasting: Advanced time-series forecasting models (like Q-Predict) analyze historical patterns, seasonality, and external signals to generate accurate, SKU-level demand and inventory forecasts. This enables proactive planning, reduces stockouts, and minimizes excess inventory.
Route Optimization and Logistics Planning: Real-time AI pipelines adjust shipping and delivery routes based on live data—such as traffic, weather, or port congestion—ensuring timely, cost-efficient transport while reacting to disruptions as they unfold.
Supplier and Vendor Risk Monitoring: Multimodal AI models assess supplier performance, extract insights from contracts and communications, and continuously monitor for geopolitical for ESG-related risks. This enables early warnings and better sourcing decisions.
Warehouse Automation: AI systems, integrated with robotics and vision models, automate picking, sorting, and restocking tasks. Anomaly detection ensures operational accuracy, while adaptive learning helps warehouses scale efficiently in dynamic environments.
Anomaly Detection and Exception Handling: Machine learning models detect anomalies across the supply chain—from production delays to inventory mismatches or transportation exceptions. Alerts and corrective actions are automatically triggered through connected systems.
Language and Communication Intelligence: SUTRA’s multilingual reasoning capabilities enable understanding across 50+ languages. AI automates translation, summarization, and extraction from emails, shipping forms, and customs documents—streamlining global communication and documentation.
Aligning strategy with operational execution—intelligently and at scale
01 / Forecasting with Precision
Modern supply chains are exposed to volatile demand patterns, geopolitical disruptions, and fluctuating lead times.
Q-Predict, powered by SUTRA, delivers fine-tuned, multivariate time-series forecasting for inventory levels, demand signals, shipment delays, and supplier performance—using your historical data, external signals, and market indicators.
→ SKU-level demand forecasting
→ Inventory optimization
→ Supplier lead time prediction
→ Seasonal pattern recognition
→ Real-time reforecasting
02 / Visibility Across Languages and Formats
Global supply chains rely on documentation, conversations, and contracts in dozens of languages and unstructured formats.
SUTRA’s multilingual reasoning models bring native understanding to over 50 languages—extracting insights from customs forms, email threads, invoices, and supplier updates, while maintaining accuracy in low-resource settings.
→ Multilingual document parsing
→ Email summarization and alerting
→ OCR + reasoning for shipment documents
→ Compliance document understanding
→ Vendor-side support automation
03 / Integrated Planning & Execution Loops
Supply chains are systems of decisions—when to ship, reroute, produce, or restock.
AIRe enables orchestration of AI-enhanced decision workflows that integrate seamlessly with ERP, WMS, TMS, and PLM systems. Through modular AI runtimes, decisions are executed as part of the data pipeline—with full auditability and enterprise control.
→ Dynamic reorder points
→ Autonomous PO and invoice reconciliation
→ Adaptive safety stock buffers
→ Transportation re-routing
→ Supplier risk mitigation
04 / Secure AI at the Edge and Across the Cloud
With suppliers, partners, and operations distributed globally, supply chain systems need both flexibility and control.
AIRe supports edge-deployable, inference-efficient D3 models tailored to your domain, enabling localized intelligence with enterprise-grade governance—whether in the cloud, on-premise, or at warehouse nodes.
→ D3-Supply: compact, domain-tuned models
→ Edge-compatible inference
→ Governed AI with data residency compliance
→ Secure connector framework for supply chain data
→ Hybrid architecture support
Where We Power Intelligence in Supply Chain
01 - Manufacturing & Production
Enable smart planning and dynamic execution with predictive inputs and real-time monitoring.
→ Yield and scrap forecasting
→ Predictive maintenance
→ Line scheduling optimization
→ Sensor data anomaly detection
02 - Logistics & Transportation
Boost reliability, reduce delays, and react faster with AI-powered coordination.
→ Route optimization
→ Delay and exception prediction
→ Load balancing
→ Freight cost prediction
→ ETA reasoning across multimodal carriers
03 - Procurement & Sourcing
Anticipate supplier risks and streamline vendor collaboration with multilingual understanding and data fusion.
→ Supplier reliability scores
→ Vendor document processing
→ Supply-side RAG (retrieval-augmented generation)
→ ESG data extraction and alignment
04 - Retail & Distribution
Balance inventory across channels with AI that adapts to changing demand and fulfillment trends.
→ Omnichannel demand planning
→ Last-mile delivery forecasting
→ Promotion-aware inventory strategies
→ Stockout prevention
05 - Enterprise IT & Analytics Teams
Build, adapt, and monitor AI pipelines without managing underlying model infrastructure.
→ Model swap via unified API
→ Pluggable data connectors
→ Dashboard and observability tools
→ Continuous model distillation with enterprise data
SUTRA in Supply Chain
Predictive Inventory Rebalancing
Customer: Global Consumer Goods Manufacturer
Challenge: Regional warehouses were frequently overstocked or understocked, impacting fulfillment rates and inflating carrying costs.
Solution: Using Q-Predict models trained on sales, logistics, and external trend data, the system generated daily inventory rebalancing recommendations. SUTRA-based workflows triggered PO updates and transportation requests through ERP and TMS integrations.
Impact:
→ 30% reduction in stockouts
→ 22% decrease in inventory holding costs
→ Automated decision flows across planning and execution systems
