Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Collect and extract posts, comments and user profiles on Parler.
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 Parler with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Effective enterprise integration requires diverse data inputs. Web data—whether from partner ecosystems, proprietary systems, or public sources—offers the scale and flexibility needed to drive data pipelines.
Datastreamer lets you accelerate your data usage by applying operations like structuring, enriching, joining, and filtering—choose from hundreds of prebuilt, plug-and-play options.
Supercharge your data workflows with Datastreamer. Add flexibility to your Pipelines and put an end to the common bottlenecks in handling web data.
Add Datastreamer components to your data stack and explore its full capabilities
