Media and broadcast companies are in the midst of a profound transformation. Ever-increasing amounts of content, ever-shorter production cycles, and growing demands on metadata, versioning logic, and security are placing a heavy burden on post-production teams. At the same time, artificial intelligence is becoming increasingly important—especially where repetitive processes cost time and block creative potential.
The good news is that modern workflow automation with AI modules is already powerful and reliable today. But it is also clear that current systems are reaching their limits – at the latest when complex decisions or flexible planning processes become necessary.
This is where the shift to agentic process automation begins – the next step in which AI not only supports but acts independently.
But what is possible today with AI-based workflow automation?
The level of automation in media and broadcast workflows has increased significantly in recent years. With the help of AI modules, numerous tasks can now be handled reliably, scalably, and consistently—both on-premises and in hybrid scenarios. One of these examples is our Dubidot integration, using their internal workflow engine for processing tasks automatically:
Typical Use Cases:
Ingest and Media Preparation:
- Automatic detection of new assets in storage
- Proxy generation & technical standard checking
- Automatic creation of project and folder structures
- Assignment of metadata based on file names, formats, or templates
As powerful and reliable as modern workflow systems are, they ultimately remain rule-based—meaning that AI works according to fixed rules and only responds to human input.
This means that media workflows lack the ability for AI to make complex decisions and act intelligently and autonomously on several tasks. Even if the input from a human user is unclear, an Agent System can still take it, extract the intended meaning, suggest a solution and automatically carry out the necessary processes in parallel.
MCP as a game changer: The key to truly autonomous agentic AI workflows
Combined with Agentic AI you can take it a step further. Agentic AI automation systems are often based on the open MCP standard, enabling them to understand goals and decide independently on the next necessary steps.
Why does MCP play such an important role at Agentic AI?
The Model Context Protocol (MCP) is an open standard adopted first by Anthropic and later by OpenAI and others. It defines how AI models communicate with external tools, data sources, and systems.
This is an important step in giving agentic AI the ability to independently perform necessary actions.
The MCP provides the necessary layer to:
With DeepVA, we offer powerful workflow automation to efficiently and reliably automate recurring media processes such as analysis, metadata enrichment, and post-production.
By adding Agentic AI Workflows, we will be able to offer our customers solutions that not only automate tasks, but also make decisions, plan, and actively use the appropriate tools independently—for even more flexible, adaptive, and context-aware production processes.
Want to take the next step in the AI journey?
Someone always needs to lead the way, and we would be happy if you were interested in accompanying us on this journey. Would you like to explore the future of agent-based workflow with us? Or do you have any questions? Contact us!
