Broadcasters & Publishers
How Asharq Network automated media archiving to reclaim time
Automating interview archiving with AI to reduce manual workload and give teams time to focus on what matters

The situation

Asharq Network, a leading Arabic-language multi-platform news channel, produces a high volume of digital content daily, including remote interviews with guests viaZoom. Like many modern broadcasters, Asharq Network faced a familiar challenge:managing a growing volume of content in an efficient and scalable way.

The manual process of archiving interviews was slow, resource-heavy, and kept skilled staff in library and media management tied up with repetitive tasks.

This initiative marked a shift toward more automated media operations and increased efficiency, setting the stage for measurable improvements in time and resource allocation.

The challenge

Scaling archiving: managing daily workloads

A well-run archiving process is essential in broadcast media. It supports content reuse, compliance, and institutional knowledge. But inefficient workflows do more than consume storage; they place unnecessary demands on people’s time.

For Asharq Network, this showed up in the daily task of archiving DTL (Down-the-Line)interviews. These remote recordings can run an hour or more, even when only a few minutes were needed for airing or archiving.

A daily strain on team resources

Before automation, the library and media management team had to review and trim each full-length recording manually. The multi-language nature of the interviews added to the complexity and slowed things down even further.

Tangible business impact

This manual workflow created two primary pain points with a direct and measurable impact on the business:

Time and resource drain: The team spent 5 to 7 hours a day on repetitive trimming tasks, diverting attention from more strategic work. Time and resource drain: The team spent 5 to 7 hours a day on repetitive trimming tasks. Valuable time that added up fast and took attention away from higher-value operational work.

Workflow complexity: Isolating relevant segments from long, multilingual recordings required careful review and manual precision, increasing the operational burden.

Asharq needed a smarter way forward. One that would reduce manual effort and make its operations more scalable.

The qibb team moved very quickly. We shared our requirements, and the initial implementation was completed within a few days.

Kathey Battrick, Head of Media Management and Library

The solution

Workflow diagram
From ingest to archive: qibb orchestrates transcription, AI segmentation, and human validation to prepare interview clips for archive.
An integrated agentic workflow

To overcome their archiving challenges, Asharq Network partnered with qibb to design a workflow that combined automation with AI. At the core was an agentic system, a workflow orchestrator that connects and manages tasks across multiple tools, managing the full process from transcription to archiving.

This was not just about fixing a step in the process. It was a chance to rethink the workflow entirely, giving time back to the library and media management team and creating a more efficient and focused archiving process.

Strategic partnership and technology stack

Using qibb’s low-code platform, the solution was quickly developed and integrated with Asharq Network’s existing tools: Mimir, OpenAI, MicrosoftTeams, Trint, and Avid Media Central Cloud UX.

The result was a fully automated system, built specifically around Asharq Network’s archiving needs.

Ingest
A new interview is added to Mimir. qibb is instantly notified and starts the process.
Transcription and AI segmentation
Trint creates a transcript. qibb uses OpenAI to identify and extract only the relevant speech segments, regardless of language.
Human in the loop
A rough-cut is generated in Mimir. The team is notified via MS Teams to approve or adjust the sequence.
Archive and clean-up
The approved clip is rendered and sent to Avid for archiving. The full-length file is deleted after 7 days to save storage space.

The implementation

From concept to reality in days

Speed matters. Asharq Network did not just want a solid solution; it needed one that could be deployed quickly and start delivering value fast.

qibb’s low-code flexibility made it possible. The entire workflow was implemented, tested, and operational in just a few days, with minimal disruption to media management operations.

We’re saving hours of manual work across the team, which has made a real difference to how we operate. It’s been one of my favorite AI initiatives this year.

Kathey Battrick, Head of Media Management and Library at Asharq Network

The results

How Asharq reclaimed time and focus

The automation initiative delivered immediate, measurable impact. Asharq Network reduced manual compilation work by 66% on average, allowing its team to reclaim hours previously lost to trimming interviews. These results went beyond operational gains. They gave the library and media management team more time to focus on creative, high-value tasks.

Ready to reduce manual work and save storage?

Learn how qibb can help modernizeyour media workflows with low-code automation.

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