FOR SOCIAL LISTENING PLATFORMS
Connect and enrich social media sources
Ingest, enrich, and route social media sources, all without building or maintaining fragile pipelines.
Datastreamer is what engineering teams use when building social listening platforms that need to ingest, normalize, and enrich high-volume, unstructured data from social media, forums, blogs, and reviews.
Instead of managing brittle APIs, scrapers, or schema drift, teams rely on Datastreamer to deliver structured, enriched, and production-ready content into their analytics, dashboards, and client-facing products.
How Datastreamer supports social listening platforms
- Ingest from any social or open web sources
- Enrich with topics, sentiment, and video analysis
Apply sentiment, emotion, brand, product, or custom tags with plug-and-play components.
- Real-time streaming into your stack
Route enriched data into your systems via real-time or batch delivery.
- Abstract away ingestion complexity
Built for teams that need more than scrapers & scripts
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
Social -> Sentiment Enriched
Social Posts -> Brand Health
Use real-time topic or brand mentions, combined with NLP enrichments to power brand reputation monitoring.
Raw Signals -> User Alerts
Niche Sources -> Coverage+
Enriched Content -> Analytics
Blogs -> Usage Ideas
Enrich campaign strategies by discovering novel usages and applications of existing products.
Why product and engineering teams use Datastreamer
Whether you’re building real-time sentiment dashboards, brand health trackers, or social research tools, Datastreamer makes external data ingestion reliable, consistent, and production-ready.
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
Data pipelines for SI platforms
Using Datastreamer, your engineering teams can rapidly deliver the data pipelines for complex use cases, reducing speed-to-launch of new features by 85%
FAQ’s
Anything from social platforms, review sites, forums, other SI platforms, SERP data, trend tools, or your own feeds. Datastreamer handles structured and unstructured inputs.
With over 38,000 ready-to-use capabilities, it's very easy to meet every ask.
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 through APIs.
Yes, many customers use pipelines running in Datastreamer that either feed from, or are supplemental to, social listening platforms.
Some common pairings include: Meltwater, Sprinklr, Brandwatch, Brand24, Talkwalker, and others. These usages are often derived from requiring customization or expansions beyond offerings from those platforms.
We abstract each source into a common schema, so your downstream systems don’t have to handle structural drift, missing fields, or format mismatches.
Yes. Datastreamer detects language, supports multilingual content, and handles formatting and encoding issues out of the box.
While compliance requirements can be quite broad and use-case specific, Datastreamer has a wealth of data processing, PII detection, redaction, hashing, and other capabilities that you can use in your pipelines.
Faster time to market, no ongoing maintenance, and a much lower risk surface for managing content ingestion and normalization.
