Inventory Forecasting for Logistics

Custom ML models that identify stockout risk before it reaches operations. 

• SKU-Level Forecast Granularity. Forecasting runs at the individual SKU level, not only by product category. The algorithm accounts for each SKU’s movement patterns, including seasonal tails, cannibalization between similar items, and differences in demand elasticity. 

• Continuous Retraining Pipeline. The model is not static. It retrains automatically on new data at defined intervals, so when market behavior shifts sharply—a tariff shock, a supplier disruption, a change in consumer patterns—the system adapts without manual analyst intervention.

• Forecast Accuracy Dashboard. The dashboard shows where the model is least accurate, helping operations teams prioritize manual review, refine assumptions, and improve forecast quality over time. See how we centralized fleet data to improve planning, reporting, and readiness for predictive analytics. 

Connect your enterprise ERP systems to predictive supply chain platforms without ripping them out.

• API Bridge Architecture. We build robust bridges between legacy systems and modern modules, enabling real-time communication without altering the core ERP. 

• Multi-System Data Normalization. Implement canonical normalization to unify disparate data formats without signal loss.

• Legacy Module Decomposition. We decouple legacy monoliths into scalable microservices without full-scale rip-and-replace.

• Integration Health Monitoring. After launch, a monitoring dashboard is deployed that tracks the status of all integration connections, delays, synchronization errors, and anomalies in data flows. The problem is identified automatically before it affects operations. 

One dashboard for every SKU, across owned warehouses, 3PLs, and in-transit stock 

• Unified Inventory Data Layer. We consolidate all global supply chain nodes into a single database via API integrations. A manager sees the real balance for each SKU in every location without needing to log into five different systems.

• In-Transit Stock Tracking. Cargo that has already been shipped by the supplier but not yet received at the warehouse is displayed as a separate category with a predicted arrival date. 

• Environmental Sensor Integration. The platform tracks real-time location and condition data, generating alerts for any deviations from required storage parameters. 

• Multi-Location Inventory Rules Engine. Different locations can have different reservation rules, minimum balances, and replenishment algorithms.

• Stock Anomaly Alerting. The system automatically detects anomalies, a sharp drop in balances, inconsistency between book and physical inventory, and suspiciously slow product rotation. Alerts are sent to responsible parties before the anomaly turns into a stockout or frozen capital. 

Auto-generate POs based on next-gen demand planning, dynamic reorder points, lead times, and supplier performance.

• Dynamic Reorder Point Calculation. The reorder point for each SKU is calculated not as a fixed number, but as a variable value, based on the current sales rate, lead time variability, and set service levels. When market dynamics change, threshold values are recalculated automatically. 

• Supplier Lead Time Variability Modeling. The system accumulates the history of actual order fulfillment times for each supplier and takes into account their variability when calculating safety stock. If a specific supplier regularly delays deliveries by 3-5 days, this is embedded in the logic, not ignored. 

• Automated PO Generation & Routing. Upon reaching a threshold level, the system automatically generates an order draft with filled positions, quantities, and suppliers and directs it for approval to the responsible person. 

• EDI and Supplier Portal Integration. Generated orders are transmitted to suppliers via EDI protocols or a custom portal without email correspondence and manual entry. Confirmations, lead time changes, and shipping notices are returned to the system automatically and immediately affect the availability forecast. 

• Replenishment Performance Analytics. A separate module tracks the efficiency of the entire replenishment cycle, the percentage of orders completed on time, average deviation from calculated lead time, and frequency of emergency purchases. 

Track on-time delivery, spec compliance, and ESG requirements across your entire vendor network. 

• Supplier Scorecard Engine. For each supplier, the system automatically calculates a scorecard based on actual data, percentage of on-time deliveries, compliance with specifications, and frequency of discrepancies in documentation. The score is updated after every transaction, not once a quarter during a manual audit. 

• Regulatory Compliance Monitoring. The system monitors indicators related to customs and industry standards across the supply chain, identifying risks before they affect cross-border movement. 

• Multi-Tier Supplier Visibility. Transparency is built not only at the level of direct suppliers but also at the level of their sub-suppliers, where traditional systems no longer see anything. 

• ESG Metrics Integration. Tracking of ESG indicators for suppliers, carbon footprint, compliance certificates, and social audits is built into the dashboard. 

• Automated Supplier Risk Alerting. The system monitors external signals on suppliers, financial instability, lawsuits, and news of production disruptions and automatically raises the risk level in the supplier profile. The procurement team receives an alert and can proactively seek an alternative without waiting for an actual delivery failure. 

Outgrown your legacy inventory software? We rebuild it as your asset, not their subscription.

• Data Migration & Cleansing Pipeline. We cleanse historical data, SKUs, transactions, balances, and suppliers of duplicates and contradictions before transfer, not after. Dirty migration data is one of the main reasons ERP projects fail, so this stage runs as a separate engineering process with verification at every step.
• Feature Parity + Custom Logic Layer. The new platform recreates all the necessary functionality of the previous system, but it does so on top of business logic that SaaS wouldn’t let you implement—specific pricing rules, non-standard units of measure, and location-based reservation algorithms. The company receives not just a replacement, but a tool that finally works the way the business needs it. 

• Parallel Run & Cutover Strategy. The new system runs parallel to the old one for a defined period. Both receive the same data, and the results are compared. The transition occurs only after the new platform confirms accuracy and stability, which eliminates the big bang operational risk. 

• TCO Modeling & Ownership Transfer. Before the project begins, the client receives a detailed model of the total cost of ownership, comparing current SaaS subscription costs with the cost of development and support of a custom platform over a 3-5 year horizon. The platform transfers to the company’s balance sheet as an asset, rather than remaining a rented tool with annual price growth. 

Real-time environmental and location monitoring for specialized logistics

• Chain of Custody Documentation. Every event in the chain, transfer between carriers, change in storage conditions, and customs clearance is automatically recorded with exact time, location, and responsible party.  

• Carrier & 3PL Compliance Monitoring. The platform tracks compliance with temperature conditions not only at owned facilities but also in carrier vehicles and 3PL partner warehouses via integration with their telematics systems. If a carrier violates conditions, the incident is recorded automatically and becomes part of their scorecard. 

• Regulatory Report Automation. Reports for regulatory bodies, temperature logs, compliance certificates, and documentation on deviations are generated automatically in the required format.