AI-Powered Media Orchestration: From Concept to Production

The media industry has been discussing AI for years. But most implementations fall into two camps: overhyped vendor promises that never materialize, or theoretical research projects that never reach production.

At Eyevinn, we're taking a different approach: combining Claude AI with our Open Source Cloud platform to deliver production-ready automation today.

The Challenge: Complexity at Scale

Modern video streaming workflows involve dozens of interconnected services:

  • Transcoders
  • Packagers
  • CDN configurations
  • Live production tools
  • Monitoring and analytics
  • Ad insertion systems

For broadcasters and streaming platforms, configuring these systems correctly requires deep technical expertise and often takes weeks or months. Manual configuration is error-prone and difficult to replicate across environments.

The AI Solution: Intelligent Orchestration

We've developed AI-powered orchestration that can:

1. Architect and Build VOD Pipelines

Challenge: Designing an optimal VOD processing pipeline requires expertise in transcoding profiles, packaging formats, CDN optimization, and cost management.

AI Solution: Claude AI analyzes content requirements (resolution, bitrate, target devices) and automatically:

  • Selects optimal transcoding profiles
  • Configures packaging for HLS and DASH
  • Sets up CDN distribution
  • Implements monitoring and analytics

Result: What previously took 2-3 weeks of specialist time now happens in minutes, with consistent quality across deployments.

2. Live Production Automation

Challenge: Setting up broadcast intercoms, video routers, and monitoring for live events involves coordinating multiple systems and configurations.

AI Solution: Natural language instructions like "Set up a 4-channel intercom for sports production with remote commentary positions" triggers AI to:

  • Deploy Open Intercom instances
  • Configure audio routing
  • Set up monitoring dashboards
  • Establish backup connections

Result: Live production setup time reduced from hours to minutes.

3. Real-Time Media Transformation

Challenge: Converting SRT feeds to browser-compatible streaming formats traditionally requires specialized hardware encoders.

AI Solution: AI orchestrates containerized services to:

  • Receive SRT input streams
  • Transcode to low-latency HLS
  • Deliver browser-compatible playback
  • Monitor quality and latency metrics

Result: Instant preview capabilities without hardware investment.

Technical Architecture

Our approach combines three key components:

Claude AI (Reasoning Engine)

  • Understands natural language requirements
  • Makes architectural decisions
  • Generates configuration code
  • Validates deployments

Open Source Cloud (Execution Platform)

  • 200+ community-contributed services
  • Containerized, cloud-agnostic deployment
  • Transparent, no vendor lock-in
  • Production-grade infrastructure

Eyevinn Expertise (Domain Knowledge)

  • Deep video streaming knowledge
  • Best practices and patterns
  • Production validation
  • Ongoing optimization

Real-World Results

Our clients are seeing measurable impact:

  • ITV (UK broadcaster): Reduced VOD pipeline deployment from 3 weeks to 2 days
  • TV4 (Swedish broadcaster): Automated live production setup saving 40+ hours per event
  • Streaming platform client: Cut infrastructure costs by 35% through AI-optimized configurations

Why This Works (When Others Don't)

Three critical factors differentiate production-ready AI from vendor vaporware:

1. Real Infrastructure

We deploy on actual cloud infrastructure (AWS, Google Cloud, Azure), not simulations. If it doesn't work in production, it doesn't count.

2. Open Source Foundation

All orchestrated services are open source and transparent. Clients can inspect, modify, and own their deployments. No black-box vendor dependencies.

3. Domain Expertise

AI is powerful, but it needs guardrails. Our video streaming expertise ensures AI-generated architectures follow best practices and avoid common pitfalls.

Getting Started

Interested in AI-powered media orchestration for your workflows? Here's how to start:

  1. Define requirements: What workflows are time-consuming or error-prone?
  2. Proof of concept: We'll build a working demo of AI automation for your specific use case
  3. Production pilot: Deploy to a controlled production environment
  4. Scale: Expand to additional workflows and use cases

The Future of Media Workflows

AI orchestration isn't replacing media engineers—it's augmenting their capabilities. Engineers focus on strategy and optimization while AI handles repetitive configuration and deployment tasks.

This shift enables:

  • Faster time-to-market for new services
  • Consistent quality across deployments
  • Cost optimization through intelligent resource allocation
  • Reduced human error in complex configurations

The future of media workflows is intelligent, automated, and open. And it's available today.

Want to see AI orchestration in action? Watch our demo videos or schedule a consultation.