tech, media & telecom.

Industrial Generative AI for
Technology, Media & Telecommunications

Industrial Generative AI is transforming the tech, media & telecom landscape, enabling service providers to be more targeted, efficient, agile, and responsive in their operations. Generative AI could deliver a $140-230B annual impact across telecommunication, media and entertainment, according to McKinsey.

Use Cases

Real-time applications for Tech, Media & Telecom’s most complex industrial-scale challenges

Anomaly Detection

LLM Retrieval

Optimization

Predictive Modeling

Virtual Sensors

Anomaly Detection

LLM Retrieval

Optimization

Predictive Modeling

Virtual Sensors

Key Challenges


Detect unusual or anomalous events with greater accuracy than traditional algorithms by leveraging generative models and quantum techniques.
  • Identifying potential threats before they disrupt services 
  • Flagging potential equipment or infrastructure failures more quickly and accurately 
  • Accurately classifying an audio or visual signal with as few data points as possible 

Zapata AI Solutions


Network Threat Prediction & Detection

Adapt to changing network patterns and flag potential threats using a generative model trained on baseline network activity, past attempts, and intrusions.

Predictive Maintenance

Prevent system failure and proactively identify early warning signs of malfunctions.

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How can these solutions work for your enterprise?

Capabilities for Tech, Media & Telecom

Sensor Fusion

Combine insights from various sensor channels to add redundancy and infer data for variables that would not be measurable with conventional sensors.

Optimization

Find more efficient or more timely solutions to complex optimization problems using the latest insights hidden in live data streams.

Anomaly Detection

Detect unusual or anomalous events with greater accuracy than traditional algorithms by leveraging generative models and quantum techniques.

LLM Retrieval

Accelerate incident response by creating a conversational chat interface with large language models (LLMs) to interact with live and historical sensor data.

Predictive Modeling

Predict network demand, maintenance needs and more with predictive models enhanced with synthetic data.