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Industry · Logistics & Supply Chain

Logistics technology built for
operations that cannot afford to stop.

Logistics and supply chain operations run on some of the oldest, most complex technology stacks in enterprise. The WMS installed in 2006, the TMS nobody has touched because everyone is afraid to, the batch jobs reconciling data between systems that were never designed to talk to each other. Shelorve has worked inside these environments — and has the delivery record to show it.

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The Challenge

What makes logistics technology hard

Legacy WMS and TMS debt
Warehouse and transportation management systems installed 10–20 years ago carry business logic accumulated through years of customization, patching, and undocumented integration. Replacing them requires understanding them completely — including the integrations that only exist in configuration files nobody has opened in years. The dependency landscape is almost never what the documentation says it is.
The stop-shipment risk
A failed WMS migration does not slow down a process — it stops shipments. In logistics, a production outage is measured in hours: customer commitments broken, carrier bookings missed, penalty charges triggered. This makes the evidence-first approach essential. You do not get to discover surprises in production.
Data that exists but is not being used
Logistics operations generate enormous volumes of telemetry — fleet location, warehouse sensor readings, dock utilization, carrier performance, route efficiency. Most organizations are not using it analytically. The data pipeline infrastructure to make it useful for forecasting and optimization does not exist. The decisions being made without it are costing more than the infrastructure would.
ERP and WMS integration failures
Inventory figures in the ERP do not match physical counts in the warehouse. Order status in the customer-facing system lags behind the actual production state. These are integration architecture problems, not data quality problems — and they have specific, addressable causes.
What We Deliver

What we deliver for logistics and supply chain organizations

WMS & TMS Modernization

Evidence-led migration from legacy WMS and TMS platforms to modern cloud-native architectures on AWS. Every integration mapped before any migration work begins. Zero stop-shipment events by design.

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AI Demand Forecasting & Optimization

ML forecasting models trained on historical order data, seasonal patterns, and external demand signals — connected directly to inventory and replenishment systems. Route optimization, carrier selection, and predictive warehouse equipment maintenance. Typical forecast accuracy improvement: 30–40% versus rules-based approaches.

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AWS IoT Data Platform

Real-time telemetry ingestion via AWS Kinesis from fleet telematics, warehouse sensors, and dock management systems. S3 data lake for historical analysis. The operational data foundation for real-time decision-making and longer-term optimization.

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Salesforce for Carrier & Customer Operations

Sales Cloud for carrier relationship management. Service Cloud for shipment tracking, exception management, and claims. Connected to WMS and TMS via MuleSoft — so the Salesforce view reflects real operational status, not a delayed or disconnected record.

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Stop-shipment events during WMS migration
30–40%
Forecast accuracy improvement over rules-based forecasting
Real-time
ERP and WMS inventory data in sync — no reconciliation reports needed
Logistics & Supply Chain · Common Questions

What logistics and supply chain leaders ask us before they engage

Every WMS migration begins with a complete dependency assessment of the existing environment — every integration, every batch process, every scheduled job, including the ones not in any documentation. The migration is sequenced to bring new functionality online in parallel with the existing system. Cutover only occurs once each component is confirmed stable in production. We do not do big-bang WMS cutovers.
Demand forecasting and inventory optimization typically deliver the highest ROI — they directly reduce carrying costs and stockout rates. Route optimization and carrier selection come second. Predictive maintenance for warehouse equipment is increasingly viable as sensor data matures. The right starting point depends on where your largest cost and reliability problems currently sit.
Yes. Shelorve's integration experience covers SAP, Oracle, and specialist logistics platforms. We use MuleSoft for complex multi-system integrations and custom APIs where direct integration is more appropriate. The starting point is always the same: map every dependency in the current environment before designing the integration architecture.
Yes. The technology challenges facing 3PLs — multi-client WMS configuration, carrier network integration, customer portal management, billing accuracy — differ from those facing shippers. But the underlying technology debt and the need for evidence-first modernization are the same. Shelorve works on both sides.
The discrepancy between ERP inventory records and physical WMS counts is almost always an integration timing problem — data flowing between systems at different cadences, with no reconciliation logic to handle conflicts. Shelorve diagnoses the specific integration architecture causing the discrepancy and fixes it at root cause rather than running reconciliation reports around it.
Logistics and supply chain transformation

starts with understanding
what is actually running the operation.

Tell us what you are trying to solve. We understand WMS complexity, the stop-shipment risk, and the integration debt that accumulates over years of incremental change — and we have delivered in production environments where stopping the operation was never an option.

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