Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Movies, songs, memes, books, and other cultural references can be detected with this LLM-powered model in 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.
Collect and extract YouTube video and profile search results using keywords, and YouTube comments using URLs. Further refine the video and profile searches by start date and end date using additional parameters.
How Datastreamer works
Quickly apply Datastreamer Cultural Reference Recognition Model to Bright Data YouTube with a Datstreamer Pipeline.
In modern enterprise architecture, web data fuels integration pipelines by bridging internal systems with external data sources such as partner networks and publicly accessible web content.
To accelerate using your web data, you can apply any number of operations to the data. Enrich, augment, join, structure, filter, storage, search, or more! Datastreamer has hundreds of plug-and-play operations that you can apply.
With Datastreamer it’s never been easier to use web data. You can dynamically expand your Pipelines with more capabilities, and you’ve now been able to solve your operational bottlenecks in working with web data.
Add Datastreamer components to your data stack and explore its full capabilities
