ERP purchase orders. WMS fulfilment events. Carrier APIs. Supplier portals. Customs records. Each in its own schema, its own cadence, its own ID convention. qwry discovers how they relate, builds the cross-source warehouse automatically, and lets your team query it in plain English.
Every tier of the supply chain runs on a different system. The data exists, but it never talks to itself.
Purchase order IDs in your ERP don't match the shipment references in your 3PL's WMS, which differ again from the carrier's tracking numbers. Reconciliation is manual, slow, and always out of date.
By the time a missed SLA surfaces in a report, the window to intervene has already closed. Supply chain intelligence requires real-time cross-source joins, not batch exports from a single system.
Inventory sitting across warehouses, in-transit consignments, and outstanding POs live in separate systems. Without a unified view, teams over-order, stockout, or miss demand signals entirely.
Tier-2 and tier-3 supplier delays cascade into your operations before you see them coming. The data is in PO acknowledgements, goods receipts, and quality rejections, but it's never joined.
qwry joins purchase orders, despatch advice, carrier milestones, and customs events into a single timeline. Exceptions surface the moment data changes, not when someone checks a report.
On-time delivery rates, quality rejection ratios, lead time variance, all computed automatically from your ERP and quality management system with no manual data extraction.
qwry joins stock records from multiple warehouse systems with open PO quantities and in-transit shipments, giving planners a single inventory position that updates in real time.
Pull customer order patterns, return rates, and backorder history into your forecast model. The signals that predict demand spikes and stockouts already exist; they're just in separate systems.
Track promised vs actual delivery windows per carrier, lane, and SKU class. Identify systemic underperformers before they cause customer escalations or penalty clauses.
Compute true landed cost per SKU by joining purchase price, freight invoices, customs duty, and handling charges, across systems that have never shared a common product ID.
qwry samples your data sources and builds a confidence-ranked relationship graph, matching PO numbers, shipment references, product codes, and location identifiers across every system without any manual mapping.
qwry operates against your existing data stores. Nothing moves to an external warehouse. Critical for supply chains with contractual data residency obligations or sensitive supplier cost data.
When a planner asks "which supplier has the worst on-time rate this quarter?" they get an answer and the exact query against the cross-source warehouse. Every answer is auditable and reproducible.
Supply chain planners, procurement managers, and logistics coordinators query the unified warehouse without writing SQL. The platform generates and verifies the query, and returns an answer anyone can act on.
Mid-market third-party logistics and freight operators carry exactly the conditions qwry was built for: many systems, deep fragmentation, and little or no internal capacity to fix it.
You do not have a team to build and maintain integration pipelines between your TMS, WMS, billing, and customer systems — and you should not need one. qwry discovers the relationships automatically and builds the unified view without bespoke engineering.
qwry runs in your own cloud. Your customer data, your lane rates, and your commercial terms never leave your infrastructure. Critical for operators who carry contractual confidentiality obligations or data residency requirements from enterprise clients.
The relationships qwry discovers across your systems become a permanent, compounding view of your operation. Every system you add extends it. Understanding accumulates rather than evaporating every time a project ends or a person leaves.
qwry connects the data your transport and warehouse systems produce and makes the relationships between them queryable. It is not a vehicle tracking system and does not stream live positions. The value is in the analytical layer — cost, SLA, reconciliation — not live event feeds.
Each of these is a contained proof point that pays for itself, and each feeds the same compounding view of your operation.
Freight cost per shipment, per lane, per customer — joined from your TMS, billing, and fuel cost data. The kind of number that currently lives in a spreadsheet someone rebuilds each quarter.
Promised vs actual delivery windows joined from your operational data and the contract terms that set them. Which clients are in breach territory before they escalate, not after.
What was actually moved against what was billed — joined from your WMS and billing system. Disputes settled with data rather than argument, and overbilling caught before it compounds.
Customer playbooks and technical deep-dives from QWRY deployments in supply chain and logistics.
Inside the integration playbook: discovering the hidden join between SAP delivery documents, the WMS shipment IDs, and the carrier tracking API, and building the exception alert that nobody had been able to build before.
Read the case studyHow qwry's sampling engine resolves vendor codes, PO references, and GRN identifiers across SAP, Oracle, and spreadsheet-based supplier portals, creating a live supplier graph with no data warehouse project.
Read the deep-diveMost supply chain visibility tools display data from one system beautifully. The disruptions that matter (the ones that cascade) only appear when you join signals across ERP, WMS, and carrier data simultaneously.
Read the postDeeper coverage for specific verticals where the data fragmentation problem has a distinct shape.
A direct technical conversation with the founding team. No sales deck. Tell us about your ERP, WMS, and carrier systems and we'll map out what becomes possible when they behave like one.
Email goes directly to the founding team. First response within one business day.