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A Simple API for Complex Data:
Standardize data structures with automated transformations.
Fill the holes in your metadata with the power of Generative AI.
Instantly deploy specialized NLP models to filter & refine data.
Pre-built integrations to databases and top data vendors.
Purpose Built for Diverse Data:
AI-Driven ETL
Real-Time Streaming
Searchable Storage
Multi-Source Ingestion
We Help Data Teams Build Products Faster:
For platforms that offer threat alerts or proactive risk reports.
For teams preparing data for custom LLMs or predictive models.
For intelligence teams that deliver insights to law firm stakeholders.
For social listening tools that analyze consumer trends for R&D insights.
Unify Diverse Data to Enable:
Federated Queries
Real-Time Monitoring
Database Storage
AI Model Training
Learn More:
For intelligence teams that drive insights for lawyers and business leaders in their firm, Datastreamer saves you months of engineering work when integrating external data suppliers – so you can focus on ROI instead of ETL.
We help legal intelligence teams build products like:
An intelligence team looking to streamline the research process may want to build a custom search interface that pulls from different legal sites, web data aggregators, and databases to extract relevant information for case strategy.
An intelligence team might aim to proactively feed opportunities for business leaders to pursue by developing an automated alert system that notifies the firm of changes to tax regulation, corporate scandals or M&A activity to ensure a prompt awareness of market triggers.
An intelligence team aiming to enhance competitive intelligence might seek to develop a monitoring system that continuously tracks competitor activities across multiple online platforms, including legal news sites, social media, and court record databases.
Building pipelines for each unstructured data source can take 720+ hours of engineering time 1
Different sources deliver data in diverse formats. Unifying structures through custom scripts and manual normalization drains engineering time.
Unstructured text requires NLP or other ML models to refine data for faster extraction, or expand insights with added context in the metadata.
Integrating massive real-time data streams takes weeks of work from technical teams, leading to a piled-up backlog of integration efforts.
Sustaining pipelines that channel data into your product require constant maintenance and heavy infrastructure to support.
Datastreamer pulls unstructured data from different sources and delivers it to your products in the structured format you need.
With automated ingestion & schema standardization, Datastreamer helps you unify data from multiple sources into a standardized format that is ready for analysis, NLP enrichment, or LLM’s.
Schema Standardization: Datastreamer excels in real-time conversion of incoming data to a standard schema.
Data Consistency: Handle various data types including text, PDFs, CSVs, and more to ensure consistency across content.
Simplify integration through pre-built connectors to databases and top data vendors, ensuring effortless connectivity and interoperability.
Managed Connectors: Pre-built connectors for select partners take minutes to integrate with zero maintenance required.
Vendor Agnostic: Plug any data supplier (or API feed) into our platform and leverage our robust pipeline management capabilities.
Datastreamer outputs organized data that is ready for enrichment, enabling contextual understanding and nuances in language for more accurate insights.
Datastreamer Components: Instantly apply pre-integrated AI models from Google, Cohere, our own data scientists, and more.
Other AI Models: Push data to other models (i.e. training your own models), with uniformity in data ensuring optimal performance.