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Onedot

Product / Service Description:

Onedot enables retailers to automate product data management through AI. Stationary retailers are catapulted into the e-commerce age and product data is prepared for online sales. Marketplaces scale the product range up to 10x faster and automatically create supplier product catalogs. This is done using proprietary, self-learning algorithms that structure and clean up product data - data standards become obsolete. Articles are automatically created in the system and then efficiently enriched. This is done through automated steps such as structuring (text extraction, categorization), integration and transformation (normalization, golden record, variant creation) of the data.

Product / service innovations in the last 12 months

Onedot created numerous proprietary algorithms, which were developed to automate the complex data preparation steps that are not feasible or highly scalable with existing methods. Running on the Apache Spark cluster computing framework, the algorithms address a litany of major data prep challenges: data ingestion, data profiling, text extraction, data cleansing, schema mapping, data integration, fuzzy matching and segmentation, data deduplication, and hierarchical multi-label classification.

What is the difference between competitive solutions?

Unlike most data prep offerings currently on the market, Onedot is not a self-service proposition: it provides data prep-as-a-service. It is ideal for organizations that have complex data prep challenges that are too time-consuming to resolve in-house. Businesses which trade products from manufacturers and face the problem of complex, expensive integration of product catalogues with their own systems will benefit from Onedot's capabilities. With integration capabilities for PIM and ERP systems, the Onedot offering is particularly adept at handling product data which typically comes in many different formats from different suppliers and manufacturers.

Additional info:

Onedot is a dataprep-as-a-service provider, focusing primarily on the needs of the commerce industry. It specializes in the preparation of product data, essentially integrating new product data catalogues into a PIM system or enriching existing product data with data from third- party sources. This model can accelerate time to results, reducing the need for internal training and modification of analytic workflows.


 

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