Normalized claim
Subtitle production time per hour of video: 15 hours decrease
could take up to 15 hours of manual work
Ateme: automated multilingual subtitle generation using Vertex AI and Gemini
Use case typeContent generationUpdated Jul 18, 2026
Ateme, a French company in video compression and delivery, automated multilingual subtitle generation with Google Cloud generative AI. After video transcoding, it triggers Vertex AI and Gemini to transcribe audio, spot timecodes, and generate subtitles, then reformats output into SRT for its Titan File platform and client workflows. The solution reduced subtitle production from hours of manual work to minutes, lowered per-hour subtitle cost to under a dollar, and improved scalability, accessibility, and profitability for video catalogs.
- Organization
- Ateme
- Industry
- Consumer & Food
- Location
- France
- Published
- July 2026
Reported outcomes
15 hours
subtitle production time per hour of videoTime & speed
1 USDsubtitle generation cost per hour of subtitles
Strategic outcomes
Risk & complianceImproved accessibility complianceMarket & geographic expansionBroader linguistic coverage and international distributionCost efficiencyMore cost-effective content value
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Subtitle generation cost per hour of subtitles: 1 USD decrease
for less than a dollar, it's possible to automatically generate one hour of subtitles
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Ateme
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Story
An internal script reformats results into SRT and integrates them into the existing Titan File platform deployed with Google Kubernetes Engine and Google Cloud Storage
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Content generation
- 2Workflow automation
- 3Language translation
- Generating subtitles for one hour of video in one language previously took up to 15 hours of manual work.
- Specialized external providers were slow and costly, limiting scalability and multilingual coverage.
- Customers often had to choose a single language, reducing international distribution and accessibility.
- Ateme added a processing step connected to Google Cloud managed services.
- Vertex AI and Gemini handle audio transcription, precise timecode spotting, and subtitle generation.
- An internal script reformats results into SRT and integrates them into the existing Titan File platform deployed with Google Kubernetes Engine and Google Cloud Storage.
- Subtitles can now be produced in minutes.
- It costs less than a dollar to automatically generate one hour of subtitles.
- The solution improves scalability, profitability, linguistic coverage, and accessibility compliance.
Architecture
Ateme's Titan File transcoding application is containerized as microservices and deployed through Google Kubernetes Engine. Media files are stored in Google Cloud Storage, then processed by Vertex AI and Gemini for transcription, timecode spotting, and subtitle generation. Results are reformatted into SRT through an internally developed script and integrated into the existing workflow.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 18, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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