FOR MARKET INTELLIGENCE PLATFORMS

Ingest, enrich, and structure the world's conversations

Power market insight and prediction engines, without needing to build and manage data pipelines.

Data ingestion without infrastructure burden

Market intelligence platforms need to continuously ingest, normalize, and enrich high-volume data from reviews, forums, social platforms, and search trends.

Instead of stitching together APIs and, dealing with enrichment gaps, engineering teams rely on Datastreamer to power their data pipelines.

Market intelligence platforms use Datastreamer to power their pipelines

Scraping, 3rd party APIs, feeds, and other data, all structured into a consistent schema you control.

Choose from hundreds of NLP (or custom logic) to enrich each piece of content before it enters your product.

Stream, filter, route, and deliver enriched data in real time or batch via S3, webhook, or database.

Spend less time on maintenance, breakage, and integrations; and more on modeling and features.

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.

Live applications by threat & risk intelligence platforms

Examples of some of the real usages by customers within their pipelines, powered by Datastreamer.

Reviews -> Sentiment Trends

This market intel platform ingests reviews across the internet, performing real-time sentiment trend forecasts.

Social Media -> Topic Clustering

Merging multiple social network channels and chatter into ISO-standardized topic clusters.

Multilingual -> Global Trends

Comprehensive routing and filtering for language-compatible entity and sentiment models for global prediction.

Social -> Location Tagging

Ingesting social media and enriching with location inference models to provide country-level filtering.

Existing tools -> Expansion

Meeting data demands by merging TalkWalker features with data pipelines of supporting data sources and models.

Blogs + Forums -> Modeling

This platform uses Datastreamer to ingest news wires and niche blogs, apply threat taxonomies, and filter for relevance.

Why product and engineering teams use Datastreamer

Enable your team to ship faster, de-risk launches, or free up engineering resources. Benefit from speed to market, reducing disruptions, and having more flexibility in your product.

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 Market Intelligence 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

What types of data can I ingest into my platform?

Datastreamer supports APIs, scrapers, feeds, and structured file drops—reviews, social posts, search data, blogs, forums, and more.

Can I apply custom enrichment or taxonomies?

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.

How is this different from a social listening tool?

Social listening tools provide you with dashboards and predefined metrics, but limit your control of the data itself. Datastreamer delivers structured data directly into your platform. You have fully control in your products over modeling, analytics, and product output.

Can I use multiple languages and regions in my pipelines?

Yes. Within your pipelines you can apply language detection, translation, and more. Datastreamer's technology supports multilingual content, and handles formatting and encoding issues out of the box.

How do you handle schema consistency across sources?

We abstract each source into a common schema, so your downstream systems don’t have to handle structural drift, missing fields, or format mismatches.

I need more capabilities than my existing vendor, can I integrate it?

Many organizations are using their pipelines to address gaps in data feeds or enrichments within leading marketing intel platforms.

Recent studies from Social Intelligence Labs have found that 30% of enterprise users seek to customize their existing stack, and an additional 50% export data for additional processing.

Where does Datastreamer sit in my stack?

You pipelines (that you create within Datastreamer) sits upstream of your dashboards and analytics tools. It replaces the ingestion and enrichment workflows with a managed service. You can also integrate your data sources, existing platforms (like Meltwater, Talkwalker, Brandwatch, Brand24, Sprinklr, etc), and existing models into your pipelines. Giving you full flexibility.

What happens if a source breaks or changes?

Datastreamer monitors source stability and versioning. When feeds change, we flag schema drift and offer automated fallbacks or alerts for quick remediation.

Is Datastreamer self-hosted or managed?

It’s fully managed. There is no infrastructure to deploy or maintain. We handle scaling, updates, and availability so your team can stay focused on building product.