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swXtch AI Router

Run AI on live media without rebuilding your infrastructure

swXtch AI Router connects live media directly to all of the world’s AI models - without breaking timing, reliability, or scale.

Every second, millions of live streams go online - from mobile devices to full-scale broadcast. Connecting those streams to AI at production quality requires solving transport, time sync, format normalization, and multi-cloud orchestration.

Examples (non-exhaustive)

Moderate Content

Detect inappropriate or harmful content

Add Captions

Generate automatic subtitles

Detect Objects

Identify and track objects in video

Create Highlights

Generate highlight reels from key moments

Translate Audio

Convert speech to different languages

Describe Video

Generate AI descriptions of video content

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Connect Live Video to AI - Without the Infrastructure Headaches

Unified Interface

Connect any live media to any AI model in minutes, not months

AI Model Marketplace

Discover, compare, and test models quickly

One Credit System

Transport and inference covered together

One deterministic media fabric to Ingest broadcast video, preserve timing, distribute at scale, and run inference anywhere.

See it in action below.

Step-by-Step Process

AI Router is an infrastructure software platform that automatically builds and runs AI video processing pipelines in real time.

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All the complex technical stuff is hidden - you just see the results.

  • Shorten Experimentation

  • Reduce Engineering Burden

  • Accelerate Time-to-Production

Benefits

Route broadcast-quality live video to AI inference across cloud, edge, and on-prem environments with time sync, multicast transport, and normalized model integration.

Infrastructure Gap in Live Media AI

Live Media AI Pipelines Are Hard to Implement

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  • Ingest fails because broadcast standards and time sync are not natively supported.

  • Transport breaks under multi-Gb live streams.

  • Deterministic live transport does not exist in standard AI infrastructure.

  • No common live interface shared with AI models.

  • Scale multiplies egress cost and complexity without end-to-end visibility.

How AI Router Solves It

End-to-End AI Media Connectivity Platform​

 

  1. Broadcast-native ingest, with support for standards and time sync.

  2. Transport remains deterministic under multi-Gb live streams.

  3. A standardized live interface connects video to any AI model.

  4. Outputs are normalized across model classes.

  5. Scale is controlled with multicast fanout and full pipeline observability.

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Production Infrastructure for Live AI

  • Universal ingest of broadcast standards including SMPTE ST 2110, SRT, NDI

  • Multicast-enabled high-bandwidth transport for parallel AI processing

  • Standardized integration layer for any AI model

  • Normalized outputs across model classes

  • Customer-accessible monitoring across the entire pipeline

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