Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Collect and extract comments, video metadata and user profiles on Poal.
Detect and identify brand mentions within text. It processes content from sources like social media, articles, and customer feedback, providing insights into brand visibility. Supporting multiple languages, this classifier is adaptable for global applications and can operate in both real-time and batch-processing environments, making it valuable for tracking brand presence at scale.
How Datastreamer works
Quickly enrich Open Measures Poal with Datastreamer AI Brand Recognition Classifier 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.
Datastreamer puts data control in your hands. Apply hundreds of operations—filter, enrich, structure, join, and beyond—to unlock the full value of your web data.
Empower your data team with Datastreamer. Expand your web data Pipelines effortlessly and clear the operational hurdles that once limited your efficiency.
Add Datastreamer components to your data stack and explore its full capabilities
