Multilingual content moderation for a European streaming platform.

A platform growing faster than its trust & safety team.

The client is a Bulgaria-based streaming platform operating across multiple European markets, each with its own language and its own obligations under the EU Digital Services Act. Moderation ran on a mix of manual review and a legacy keyword filter that caught the obvious violations but missed context, coded language, and anything that wasn't text.

The bottleneck wasn't effort. It was coverage. Manual review couldn't scale with upload volume, and the existing tooling didn't touch image or video content at all, only text. Every new market added a language the moderation stack didn't support, and every gap was a DSA exposure, not just a user-experience problem.

Three constraints that made this harder than it looked.

• Multilingual coverage. Content arrived in numerous languages and dialects, several of them poorly served by off-the-shelf moderation models.
• Modality coverage. Text-only filtering missed image and video violations entirely, and those made up a growing share of uploads.
• Regulatory exposure. DSA obligations require documented moderation decisions and a working appeals path, not just a block-or-allow switch.

Four stages. Standard Elevate AI playbook.

The engagement ran through our standard four-stage framework. Each phase had a defined deliverable and a milestone gate.

Discover (weeks 1–2). We embedded with the trust & safety team to map the existing moderation workflow and violation taxonomy. We identified which categories carried the highest risk and the lowest coverage under the current stack.

Co-create (weeks 3–6). Built a multilingual text classification pipeline alongside an image and video moderation layer. Tuned decision thresholds with the platform's policy team every week, precision first.

Build (weeks 6–11). Production integration into the upload and publishing pipeline. Added confidence-scored escalation for borderline content, an appeals workflow, and DSA-aligned decision logging.

Scale (weeks 11–14). Rolled out across every supported market and language. Documentation, handover, internal training for the policy team. Monitoring and observability in place before we stepped back.

[Note: placeholder attribution. To be updated with a real, consented quote from the client before publication.]

Why this engagement became a pattern.

This was one of the three engagements that shaped the studio's early thesis. Each one involved a regulated or compliance-heavy operator. Each one involved integrating AI capability into workflows that existing vendors had failed to handle. And each one produced a pattern that's now informing our next ventures.

Moderation that's built for the language and the modality you actually operate in, not the one a vendor optimised for, is a product category of its own. Watch this space.