There’s a workflow running right now at a broadcaster you’ve heard of. Assets moving. Deadlines ticking. A QC task that fired three minutes ago is waiting for an error description a human will have to write by hand — because the system that found the problem doesn’t know how to explain it.

Nobody in that room is thinking about how fast they could build a new workflow today. They’re thinking about why this one keeps breaking the same way.

When a new workflow needs documentation, the platform writes it from the existing structure. The kind of documentation someone would produce with two free weeks and nothing else to do — generated in minutes. Undocumented workflows are how institutional knowledge disappears.

When a workflow needs to be created from scratch, a plain-language description becomes a working starting point. The engineer still reviews it, modifies it, owns it. They start with something instead of a blank screen.

And when AI is consuming resources inside a live workflow, you can see what it costs in real time — per workflow, per task, with the ability to see where usage is spiking and whether it’s worth it. Which model runs, what it costs, when a human steps in: your operations, your rules. Not a surprise when the invoice arrives at month-end.

None of this requires someone to actively use a tool. It’s running. That’s the point.

We could have shipped AI features earlier

The reason we didn’t is the same reason the capabilities we’re showing at IBC are worth looking at: they sit on a workflow engine built for real production conditions, not demo conditions. The kind of workflows Sinclair runs. That TF1 runs. That studios and sports organisations run across the globe.

The magic button — describe your workflow, watch it build — only works if the infrastructure underneath is already solid. The same applies to every AI capability inside live production. The media supply chain is the flow of content. The operating layer is what runs it. If the operating layer doesn’t know what to do with an AI output when it’s wrong, you don’t have AI in your workflow. You have a liability.

We took the time to build the foundation. The AI capabilities in Pulse-IT and Automate-IT connect directly to the forms, workflows, dashboards and analytics components that already exist — ten years of them.

Who this is for

Two people feel this differently.

The workflow builder — the engineer or technical operations person who designs and maintains the supply chain — gets time back. Less time reconstructing logic from dead workflows, writing documentation nobody updates, or diagnosing failures with half the information.

The operations manager — the person responsible for everything running correctly and within budget — gets visibility. What is the AI doing? What is it costing? Is the 2am ingest running the way it should, or is something quietly going wrong?

Most AI tools in this industry talk to one of them. Pulse-IT and Automate-IT talk to both: the builder owns what the AI drafts, and the manager sees what the AI does while it runs.

The AI worth having in media operations is the one already running — explaining its failures, documenting its workflows, and staying visible while it works. That’s what we’ve built, and it’s what we’ll be showing at IBC.