Supply Chain & Logistics
ERP purchase orders. WMS fulfilment events. Carrier APIs. Supplier portals. Customs records. Each in its own schema, its own cadence, its own ID convention.
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Built for the solutions where data fragmentation is the operational problem.
The platform is the same everywhere: connect what you already run, resolve which records are the same entity and which fields mean the same thing, query the result in plain English. What changes by solution is the vocabulary, the systems, and the questions worth asking first.
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E-Commerce & B2B Marketplaces
Qwry.AI connects your order management, customer database, catalogue, supplier records, and logistics data, then resolves identity across them: the same customer recognised as the same customer, wherever the record lives. Operational intelligence that used to take a team of engineers becomes a question you ask in plain English.
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Manufacturing & Supply Chain
Qwry.AI resolves identity across ERP, production-floor systems, supplier records, and quality data (the same part, batch, and supplier recognised across systems that name them differently) without replacing any of them. Root-cause questions that take three days take three minutes. Cross-plant benchmarking happens in a single query.
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Power & Distribution
Qwry.AI connects SCADA, billing, metering, GIS, and consumer databases, then resolves identity across them (one consumer, one meter, one feeder, however each system records it) without replacing any of them. AT&C loss analytics, tamper detection, and demand forecasting become questions you can ask in plain English.
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FAQ
Questions about solution fit.
Qwry.AI is deployed across Supply Chain & Logistics, E-Commerce & B2B Marketplaces, Manufacturing & Supply Chain, Power & Distribution. The platform is solution-agnostic (it discovers relationships across whatever sources an estate already runs), but each of these has a documented set of use cases and connectors.
No. Qwry.AI connects to the systems already in place (ERP, MES, SCADA, WMS, billing, spreadsheets and documents) and builds a governed cross-source warehouse on your own infrastructure. Nothing is migrated and nothing is replaced.
Connecting a source is a credential and a network route, not a migration project. Relationship discovery runs over what it can see and proposes the joins; a team is reading answers across two previously unrelated systems in the same session it connects the second one.
Insights
Use cases & field notes from the data trenches.
Customer playbooks, technical deep-dives and field notes from deployments into messy enterprise estates.
Technical
JOIN dms_secondary ON erp.sku_code
→ 94% match · conf 0.94
→ 94% match · conf 0.94
Contextual data in personal care manufacturing & distribution: the context between systems is the missing asset.
Every personal care manufacturer generates data at every stage of its value chain, and cannot join it. How automated relationship discovery turns five to eight disconnected systems into cross-source answers in minutes, not days.
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ERP Secondary Sales GST
One view across distributors, billing, and compliance: how pharma distribution stops flying blind.
Secondary sales in spreadsheets. Distributor stock self-declared. Billing in the ERP. Compliance records as PDFs. How Qwry.AI connects them into one governed view, and what becomes possible when it does.
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The problem is the same.
Fragmented data is not a solution-specific condition. Tell us what you hold and where it disagrees with itself; we will show you what Qwry.AI finds across it.