• Pricing
Book a demo

Automatically tag your Mux videos with AI

Swiftask analyzes your Mux video streams in real time. Our AI agents extract key information and apply structured tags for instant organization.

Result:

Turn your video library into a searchable database, without any manual data entry.

Manual tagging is the bottleneck of your content workflow

Managing thousands of videos on Mux without a robust classification system is a challenge. Manual tagging is slow, error-prone, and expensive, preventing your teams from finding the right content when it matters.

Main negative impacts:

  • Disorganized libraries: Without consistent tags, your assets become invisible, leading to lost content and wasted storage costs.
  • Inefficient searching: Your teams waste valuable time digging through improperly indexed libraries to find specific footage.
  • Underutilized video SEO: The lack of precise metadata limits the discoverability of your content by search engines.

Swiftask automates the tagging process. By analyzing your Mux video content, our agents generate relevant keywords, themes, and descriptions instantly after upload.

BEFORE / AFTER

What changes with Swiftask

The traditional workflow

An editor finishes a video and uploads it to Mux. They must then open a spreadsheet or CMS, manually enter metadata, and hope the tags remain consistent with the team's standards.

Automation with Swiftask

The video is uploaded to Mux. The Swiftask webhook triggers. The AI agent analyzes the content, generates tags, and pushes them via API to Mux or your database. It's done before you even switch tabs.

Setting up your AI tagging pipeline

STEP 1 : Connect your Mux stream

Link your Mux account to Swiftask. Connection is established via secure API, allowing for seamless reading of your upload events.

STEP 2 : Define your tagging rules

Configure the AI based on the types of tags expected: themes, duration, content type, or industry-specific keywords.

STEP 3 : Automatic activation

Turn on the workflow. Every new video is automatically processed by the AI agent as soon as it's available on Mux.

STEP 4 : Validation and iteration

Monitor the generated tags in Swiftask. Adjust the agent's instructions to refine relevance according to your needs.

Advanced video analysis capabilities

The AI agent extracts contextual information: key events, discussed topics, video tone, and notable visual elements.

  • Target connector: The agent performs the right actions in mux based on event context.
  • Automated actions: Automatic tag generation. Intelligent asset categorization. SEO-friendly description creation. Indexing for internal search. Automated metadata updates in Mux.
  • Native governance: Swiftask offers adaptive precision: the more you use the tool, the more your tags become specific to your internal nomenclature.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-mux@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Why automate your tagging

1. Massive productivity gain

Eliminate hours of manual data entry every week for your creative teams.

2. Perfect indexing

Every video is classified according to uniform criteria, ensuring seamless internal search.

3. Boosted video SEO

Rich and precise metadata naturally improves the visibility of your video content.

4. Total scalability

Whether you handle 10 or 10,000 videos, Swiftask automation remains consistent and fast.

5. Seamless integration

Swiftask fits naturally into your existing Mux stack without changing your current processes.

Security and asset confidentiality

Swiftask applies enterprise-grade security standards for your mux automations.

  • Restricted API access: The Mux integration uses secure API keys with permissions limited to the strict minimum.
  • No data storage: Swiftask processes streams without keeping your original video files on its servers.
  • Compliance: Your automation processes are audited and traceable within your Swiftask workspace.
  • Environment isolation: Every workspace is isolated, ensuring that your tags and rules remain strictly confidential.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your video management

MetricBeforeAfter
Tagging time5-10 minutes / videoA few seconds (automated)
Tag consistencyHigh human variabilityFull standardization
Search speedSlow (manual browsing)Instant (tag-based search)
Operational costHigh (labor-intensive)Drastically reduced

Take action with mux

Turn your video library into a searchable database, without any manual data entry.

Moderate your Mux video streams instantly with AI

Next use case