Technology — Panjiva
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Technology

Technology

At Panjiva, we’re using artificial intelligence and advanced data engineering to turn global trade data into information that helps everyone - consumers, governments, and businesses of all sizes. Our technology is at the center of what we do, and the value we provide for our customers. Here are the ways we're making data work for you:

Machine Learning and Natural Language Processing

Data’s inherent value is not in number of records - good data is clean and answers your business-critical questions. Global trade data, by its nature, is highly unstructured and incredibly diverse. We design machine learning and natural-language-processing algorithms to create unified data, detect and impute missing values, develop data structure, and generate insight.

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Raw Shipment Record

Shipment Record, shown above, is included with Basic plans and above.
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Entity Resolution

We don’t want our customers to waste their time and resources looking through messy data. Our entity-resolution technology extracts the underlying supply-chain networks from global trade data, reaching across languages and country-level data sets. Entity resolution provides a fast and scalable way to remove duplicates and establish relationships, which saves time for users and makes data more helpful. We can also deploy this technology to help our enterprise customers efficiently deduplicate their data and integrate their data with ours.

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Panjiva Shipment Profile

Shipment Profile Analytics, shown above, is included with Basic plans and above.
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Insights from the Panjiva Supply Chain Graph

Our machine learning models learn from the world’s largest Supply Chain Graph. We perform sophisticated AI-based analysis across our set of over 1 billion shipment records and millions of entities to programmatically answer your questions. Our algorithms recognize patterns and detect anomalies, enabling outcomes such as recommendation of new leads, nowcasting and forecasting of trade flows, and identification of market-moving events.