Automated Workflow Automation with Ortana & DeepVA

How Ortana & DeepVA are trans­forming media and broadcast companies with superior AI

 
Post-production teams are dealing with increasing volumes of content, repet­itive delivery require­ments, and the need for highest data security standards. Many of the tasks involved, such as ingest, proxy creation, shotlisting, first assem­blies, metadata enrichment and reviewing  — are repet­itive and time-consuming but not easy to setup with the limitation of not using a cloud service at all.

In order to streamline these processes, organ­i­sa­tions require reliable automation, consistent metadata and seamless integration between sched­uling, storage, review tools and AI analysis.

The Core Challenge

Media companies often face recurring questions when planning AI innovation:

  • How can repet­itive post-production tasks be automated without losing creative control?
  • How should post-production from sched­uling to cloud review work together across several tools?
  • Can we have all necessary steps consis­tently for every episode or project?
  • How do we ensure predictable, repeatable workflow execution?

Automation is only effective when all compo­nents work together seamless.

Solution Overview: Cubix as Orches­tration, DeepVA as the AI Engine

With Ortana’s Cubix media-aware workflow engine (MAWE) with its 160+ native API integra­tions and DeepVA’s AI modules, organ­i­sa­tions can build automated post-production pipelines for any repet­itive or episodic content. Cubix providing the glue between all solutions involved:

Cubix orches­trates:

  • DeepVA for visual, audio, and contextual analysis
  • Freispace for project creation, planing and suite sched­uling
  • Iconik or Frame.io for collab­o­ration and review
  • storage (cloud/on-premise), ingest, edit platforms, and many more possi­bil­ities 

 

DeepVA analysis (via Cubix integration):

  • automatic shotlists and scene bound­aries
  • face recog­nition with custom datasets of your cast
  • object, concept and context detection
  • speech-to-text, speaker detection, subtitle drafts
  • gener­ating finished draft timeline by utilizing a safe & local-hosted LLM
 
Cubix receives DeepVA’s struc­tured, timecoded metadata or even the finished EDL and uses it to drive subse­quent workflow steps in the storage and archive as well as in the editing suite.
Workflow Automation

Example Workflow

Project Creation (Freispace) 

A new project triggers automatic suite booking and folder creation.
Cubix sets up the workspace online as well as offline.

Ingest & Proxy Creation

Incoming media is detected by Cubix, which automat­i­cally generates proxies and prepares assets for editing and reviewing.

AI Analysis (DeepVA)

Cubix sends media to DeepVA for:

  • shotlist automation
  • character/face identi­fi­cation
  • transcript gener­ation
  • visual metadata extraction

All results return in a standardised, timecoded format, guaran­teeing a predictable and consistent output for storage as well as post-production.

Automated Rough Assembly

Using this metadata, DeepVA can generate a draft edit / first assembly or bin, by combining the knowledge about your needs with the knowledge and metadata of your assets. All being processed on a local and secure LLM, without cloud based analysis.

Templates ensure consis­tency across similar projects or episodes.

Review & Collab­o­ration (Iconik or Frame.io)

Cubix publishes the first assembly or proxies to Iconik or Frame.io for immediate review. Comments and approvals can trigger further automation.

Compliance & Relia­bility

DeepVA and Cubix provide a tightly integrated compliant, scalable, and future-ready AI foundation for media companies. Regulatory require­ments, data security and AI Act principles are built directly into the API, reducing legal and opera­tional risk. Continuous model improve­ments and predictable orches­tration eliminate internal IT overhead, while a broadcaster-proven user experience ensures easy adoption in editorial and archive environ­ments. With flexible integration of new models and features, broad­casters remain fully prepared for future techno­logical and regulatory devel­op­ments.

Strategic Impact

This integrated approach enables faster editorial decisions, consistent metadata, scalable automation and the trans­for­mation of regional knowledge into opera­tional AI models — maintaining regional identity while improving production efficiency.

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