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Big Data Media Intelligence, Entity Recognition & Real-Time Broadcast Telemetry

A big data media intelligence platform processing 8–10 TB of media feeds for automated sentiment analysis, named entity recognition, and real-time newsroom insights.

Venture
A Global Media Monitoring & Intelligence Enterprise
Industry
Media Intelligence & NLP Analytics
Geography
United States
8–10 TB
Media Data Scale
Real-Time
Analysis Engine
01 / The challenge

What was in the way

A major media intelligence firm ingesting global digital publications, video broadcasts, and news feeds was overwhelmed by massive data volume and multi-language entity resolution.

  • 01Ingesting high-volume multimedia feeds exceeded legacy Elasticsearch indexing limits.
  • 02Identifying corporate brand mentions across 40 languages required automated NLP entity recognition.
  • 03PR and media relations customers required instant real-time sentiment alerts on breaking news events.
02 / What we built

The architecture, and why

Engineered a petabyte-scale distributed ingestion pipeline using Apache Kafka, ClickHouse, and PyTorch transformer models to index, transcribe, and analyze global media streams in real time.

  • Distributed Kafka streaming cluster processing continuous unstructured multimedia feeds.
  • Transformer NLP inference pipeline performing named entity recognition and multilingual sentiment scoring.
  • High-performance ClickHouse analytical datastore executing aggregated brand queries across terabytes in milliseconds.
  • Real-time customer notification engine delivering instant breaking-news alerts via webhooks and email.
03 / Production stack

What is running in production

Web DevelopmentUI/UX DesignAI DevelopmentMedia Intelligence
04 / Impact

What changed, measured

  • 8–10 TB
    Media Data Scale

    Media data processed for sentiment & entity NLP

  • Real-Time
    Analysis Engine

    Automated entity recognition and sentiment intelligence

Ventures are described by industry and geography rather than by name, so publishing never waits on a client's sign-off. Named detail replaces a descriptor whenever an approval arrives. The numbers above are unchanged either way — our delivery record is independently verifiable on Upwork.

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