FOR ENTERPRISE EVOLUTION
Expand your existing social intelligence capabilities
Datastreamer helps enterprises enrich, route, and scale social data without replacing their existing social and market intelligence platforms.
Power your social intelligence like the leading platforms do.
Your teams rely on social listening tools, but they’ve hit a ceiling. Whether you’re exporting data for deeper analysis, looking to build your own custom tool, or just want broader, faster access to real-world signals, Datastreamer can help.
Datastreamer is the infrastructure layer that powers the data pipelines behind the leading social and market intelligence platforms.
- Expand data coverage
- Enrich with topics, sentiment, and categories
Setup rules and workflows to trigger sentiment tagging, named entity recognition, or escalation rules on ingestion.
- Deliver enriched data exactly where you need it
- Integrate with, rip and replace is not required
Stream data out from platforms like Brandwatch, Talkwalker, Meltware, or stream data in for deeper analysis.
Built for the 30% that need more than scrapers & scripts
30% of enterprises are exploring building their own internal tools because they need more than what current platforms can provide.
Ready-to-use components allow complex multi-source data pipelines to be assembled in minutes. Deployment happens instantly and is fully managed, allowing low-latency, high volume processing.
Common use cases
Export -> Enrich
Enriched raw exported from Talkwalker, apply multilingual classifiers, and deliver to data warehouses.
Limited sources -> Full coverage
Custom Asks -> Adaptable
Prebuilt ingestion, enrichment, and routing are ready-to-go. Allowing quick POCs and project explorations.
Critical events -> Real-time
Generic sentiment -> Right tools
Utilize a library of sentiment models to explore intent, detailed sentiment direction, and multilingual support.
One export -> Multi department
Split and route incoming data into separate feeds and deliver into different data warehouses, streams, or pipelines.
Datastreamer integrates with your existing platforms and workflows. Your engineering teams have the ability to feed enriched data into your current stack, trigger new enrichments, build AI products, or route everything to build something entirely new.
Datastreamer is the infrastructure layer that helps your team scale.
6 weeks
reduced build time per new source or enrichment connection
$285k
average annual benefit per Datastreamer customer
6,373
average annual “people hours” of pipeline work saved
80M
average pieces of web content consumed monthly per pipeline
7+
average datasources or enrichments used per pipeline
38,000+
ready-to-deploy capabilities available in the Datastreamer registry
Your engineering teams can rapidly create the data pipelines for complex use cases. 85% faster.
FAQ’s
Datastreamer is built to work alongside tools like Talkwalker, Meltwater, and Brandwatch. You can stream data in or out, or use your new Pipelines to enhance what those platforms already do.
How Datastreamer helps social listening products.
Anything from social platforms, review sites, forums, trend tools, or your own feeds. Datastreamer handles structured and unstructured inputs.
Yes. Datastreamer has a full registry of ready-to-use NLP models. You can also use LLMs in pipelines or plug in your own logic and systems.
Yes. You can define enrichment rules, use your taxonomies, or plug in existing models.
Yes. Many enterprises use Datastreamer to power custom dashboards or workflows. Your pipelines can handle the ingestion, enrichment, and routing, so your team can focus on the interface and outcomes.
We abstract each source into a common schema, so your downstream systems don’t have to handle structural drift, missing fields, or format mismatches.
No problem. We support branching pipelines, so the same enriched data can be routed to multiple destinations: dashboards, warehouses, alerting systems, and more.
Yes, your new Pipelines can support any form of data. Your own data sources, 3rd party feeds, and social listening platforms can be used together.
Faster time to market, no ongoing maintenance, and a much lower risk surface for managing content ingestion and normalization.
