Marketing · Starter · updated 2026-10-23
Video caption translation at scale
English subtitle (SRT) files are added to a table; a workflow asks an LLM to translate them into ten languages while keeping timestamps intact, then stores the files for upload.
1Is this my problem?
International customers learn faster in their own language, and subtitles are the cheapest form of localisation.
You'll recognise this if…
- Courses only in English.
- Manual translation is slow and costly.
- Subtitle timings break.
2Is this solution worth it?
The sources describe how this is built but publish no hard results, so the figures below are our estimates.
Your ROI, with the assumptions shown
Prefilled with illustrative assumptions (3 h/week at $40/h, 80% automated, build $1,500). Change them to your numbers.
Limits and when not to build it
Skip it if: English-only markets.
- Validate the SRT structure in code; models sometimes merge lines.
- Have a native speaker spot-check key languages.
3How does it work?
One small internal tool does this for you. The same job, before and after:
Before · by hand
- SRT file added: someone notices
- Translate, preserve timestamps (by hand)
- Validate SRT format
- Save per language
- Upload to video host
Video caption translation at scaleIllustrative
- Starts automatically: srt file added
- AI: Translate, preserve timestamps
- Validate SRT format
- Save per language
- Upload to video host
✦ AI step · ● human checkpoint · ✓ automatic
Translation that respects technical terms and keeps the file format intact.
- Translate, preserve timestamps
Your tool connects to
Under the hood: flow, architecture and vendors
- When: SRT file added
- Translate, preserve timestamps
- Validate SRT format
- Save per language
- Upload to video host
Architecture
Vendors commonly used
Maturity ladder
What each level adds. Most teams start at level 1 or 2 and climb. Highlighted: where this build sits.
- Level 1Basic automation
Trigger: srt file added. Fixed rules then validate srt format, save per language, upload to video host. No AI involved.
- Level 2AI-assisted
An LLM handles the judgement step (translate, preserve timestamps) and a person reviews every output before it is used.
- Level 3Autonomous agent
The agent runs end to end on its own and only stops for exceptions. Spot-checks.
- Level 4Self-learning system
Outcomes and human corrections are logged and fed back into prompts and rules on a schedule, so accuracy improves with use.
Seen in the wild
Links checked 2026-10-23. We describe these builds from public material; we are not affiliated with these companies.
4Who can build it?
Matched on services, platforms and industries agencies list on their own sites, and on their published projects.
MakeitfutureCluj-Napoca, RomaniaWhy matched: Document processing; Marketing automation; uses Zapier, OpenAI.
Related project: Loan Prequalification Automation with AI Chatbot — We transformed loan prequalification from 7 days to 5 minutes with an AI chatbot + Make.com. Automated credit checks, verification & CRM enr…
No published price
Connex DigitalUniversal City, United StatesWhy matched: Document processing; Marketing automation; uses Zapier, OpenAI.
Related project: Actionstep Automation Services for Law Firms: 125-Firm Pilot — How one association piloted Actionstep automation services for law firms—5 templates, group training, and optional 1:1 support—to roll out t…
No published price
Nex AutomationsAhmedabad, IndiaWhy matched: Document processing; Marketing automation; uses Zapier, OpenAI.
Related project: AI Vendor Product Catalog Automation: Telegram to Shopify — How an OpenAI vision model turns unstructured vendor Telegram messages into SEO-optimized Shopify product listings. Zero manual data entry.
Published price: From $5,000
Why matched: Document processing; Marketing automation; uses Zapier, OpenAI.
No published price
Msquare Automation SolutionsThane, IndiaWhy matched: Document processing; Marketing automation; uses Zapier, OpenAI.
Related project: AI Video Automation for Automated Content Production — See how AI video automation turns Google Sheet ideas into branded videos using Make.com, OpenAI, and HeyGen for automated content production…
No published price
Kizzy ConsultingWhy matched: Document processing; Marketing automation; uses Zapier, OpenAI.
Related project: AI Content Writing Agent for Real Estate Brokerages — See how a real estate brokerage used an AI Content Writing Agent to create content faster, maintain brand consistency, improve SEO, and scal…
Published price: From $6,500
Projects, tools and prices come from each agency's own website (crawled October 2026). Not paid placements.
5What should I do next?
Questions
What does a "video caption translation at scale" automation do?
English subtitle (SRT) files are added to a table; a workflow asks an LLM to translate them into ten languages while keeping timestamps intact, then stores the files for upload.
Which tools can I use to build it?
Common choices are Zapier, Zapier Tables, OpenAI. Teams often use Zapier, Zapier Tables, OpenAI together; the right mix depends on what you already pay for. n8n, Make and Zapier can all handle the workflow steps.
How much does it cost to build?
As a rough estimate, agencies often quote $500–$2k for a first version of this workflow, plus monthly tool and AI usage fees. Your quote depends on how many systems are involved and how clean your data is.
How much time does it save?
Our estimate for a small team is about 2–5 hours a week. This is a rough guide, not a measured result; measure your own baseline before you start.
Where does AI actually help?
Translation that respects technical terms and keeps the file format intact.
Who actually runs this?
Public examples include: Zapier: how Zapier uses AI internally.
Where should a person stay in the loop?
Spot-checks.
What usually goes wrong?
Validate the SRT structure in code; models sometimes merge lines. Have a native speaker spot-check key languages.
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