April Platform Update:
Bring Your Own Data

We’re thrilled to announce a highly requested roadmap item that breaks ground in the data pipeline industry: The ability to plug your own unstructured data (or external data from any vendor) into our platform. Automate data transformation into a unified schema and leverage advanced AI models to extract value from unstructured data at scale.

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3 Easy Steps to Save Months of Time

Connecting your data sources to our pipeline can be done in 3 easy steps that take 10 minutes to perform. By plugging your data into our platform, you can run advanced queries on your previously unstructured data and utilize our powerful AI models for enrichment.

These features would normally take months to develop in-house.

For the detailed steps, view our bring your own data documentation page.

If you would like to get started, book a call with our team to get set up with an API key.

The Data Pipeline of the Future

So, how does this impact your data goals? Integrating external data into analytics products or specialized AI models has been historically difficult.

This update brings us one step closer to a data platform that completely removes the technical complexities of integrating any data source into your analytics products.

Datastreamer helps you:

  • Build data pipelines in minutes, without the hassle and upfront investment of engineering time. 
  • Unlock new data value with our advanced AI models that include sentiment analysis, PII redaction, and more.
  • Expand your data coverage with billions of external data points at your finger tips.
  • Scale with less data costs by plugging into our managed infrastructure that is optimized to handle massive volumes of text data. 

Educational Resources

Recently published, expert written articles to propel your data strategy forward.

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Article

Get More ROI from Twitter Enterprise Data

We list AI models that extend the analytical capabilities of your team. We also mention methods to reduce data ingestion costs.

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The Challenges (and Solutions) of Building Generative AI Models

This article explores how developers can overcome the challenges of feeding generative AI models with high quality data.