Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Collect and extract posts, comments and user profiles on MeWe.
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.
How Datastreamer works
Quickly enrich Open Measures MeWe with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Web data serves as the foundational input for any data pipeline. Pipelines can be powered by diverse data sources, including datasets from our partner ecosystem, proprietary internal systems, or any externally accessible web data.
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
