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Enrich Bright Data LinkedIn with Datastreamer Dialect Detection Model
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Bright Data LinkedIn
Collect and extract LinkedIn company profiles and people profiles using URLs. Returns matching company that include the location, industry, number of employee; and people profile that include the location of the user, current company, experiences, number of connections and more.
About Datastreamer Dialect Detection Model
Detect dialects of language used within content for over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
Quickly enrich Bright Data LinkedIn with Datastreamer Dialect Detection Model with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Bright Data LinkedIn
Web data is an essential component of enterprise data pipelines, enabling organizations to integrate structured and unstructured data from partner APIs, legacy systems, and public web sources.
Step 2
Add Datastreamer Dialect Detection Model to enrich
Supercharge your data pipeline! Apply operations like enrichment, structuring, joining, and filtering—Datastreamer gives you instant access to hundreds of plug-and-play data tools.
Step 3
That's it! You have just connected Bright Data LinkedIn and Datastreamer Dialect Detection Model
Say goodbye to bottlenecks. Datastreamer lets you unlock the full power of web data by giving you the tools to dynamically grow your Pipelines.