Case study
Three years of subtitling and QC for Tamil and Hindi streaming.
A streaming platform needed continuous Tamil and Hindi subtitling and QC across a growing catalog, where timing and readability are judged by every viewer, not a spec sheet.
3,100+ minutes - 2,000+ episodes - 8.5–reviewed quality on this engagement
3,100+ minutes
Subtitling
2,000+ episodes
QC
Measured outcomes
Streaming subtitling and QC
Project overview
What landed, and what made it hard.
A streaming platform needed Tamil and Hindi subtitling and QC on a continuous cadence as its regional catalog grew, delivered through a top-100 LSP under their brand.
Delivery snapshot
Streaming subtitling and QC
- Client
- A streaming platform (via a top-100 LSP)
- Service
- Subtitling and subtitle QC
- Languages
- Tamil, Hindi
- Volume
- 3,100+ minutes subtitled, 2,000+ episodes QC
- Duration
- Three years, continuous
Why this mattered
Outcome before process.
Subtitling lives or dies on timing and readability: a late cue or an awkward line is visible to every viewer, and a three-year engagement only holds if quality survives the early feedback cycles.
The problem to solve
Why the work was difficult, and what MoniSa changed in-flight.
Continuous subtitling fails when reviewers rotate, when timing and language are checked separately, or when QC drifts as episode volume climbs.
The challenge
The problem to solve
The platform needed subtitling and an independent QC pass held to one bar across three years, with the partner brand in front of the end client.
Operating response
What MoniSa changed
MoniSa ran subtitling and a separate QC lane as white-label production, with reviewer continuity and a fixed quality bar across the full engagement.
- Separate QC lane Subtitling and QC ran as distinct passes so timing and language errors were caught before delivery.
- Reviewer continuity Stable reviewers across three years kept readability and timing consistent as the catalog grew.
- White-label delivery Work shipped under the partner brand, with production handled invisibly behind it.
Results
Measured outcomes from this engagement.
The platform received 3,100+ minutes of subtitling and 2,000+ episodes of QC over three continuous years, at 8.5–reviewed quality subtitling and reviewed quality QC on this engagement.
| Subtitling | 3,100+ minutes |
|---|---|
| QC | 2,000+ episodes |
| Subtitling quality | 8.5–reviewed quality on this engagement |
| QC quality | reviewed quality on this engagement |
| Duration | Three years, continuous |
Selection logic
What protected the result.
The selection came down to whether MoniSa could source and review the work at standard, and whether that would hold across the full run.
Why the fit was real
Why the fit was real
Long-run subtitling needs a separate QC lane and stable reviewers, not a bench that re-learns timing and readability each season.
What decided the result
What decided the result
Surviving the early feedback cycles and holding quality for three years mattered more than any single batch.
What buyers can reuse
What buyers can reuse
- Subtitling quality is a timing and readability problem that only a separate QC lane reliably catches.
- A three-year engagement is proof of sustained reliability, not a one-off pass that looked good once.
- The evidence keeps the client and partner details confidential and attributes the metrics only to this engagement.
Continue from this proof
Useful comparisons for the same problem.
Use these links to compare the case with the matching service, buyer guide, and language coverage.
Mapped context
Service and buyer context
Languages named
Examples referenced in the engagement.
- Tamil
- Hindi
- Subtitle timing and QC
More proof
Related proof
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case evidence
Nearest proof pattern.
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Buyer questions
Ask the questions weak vendors avoid.
Short answers for buyers checking fit, coverage, quality method, and next-step readiness.
What was delivered on this engagement?
Subtitling: 3,100+ minutes. QC: 2,000+ episodes. Subtitling quality: 8.5–reviewed quality on this engagement
What control kept the work stable?
Surviving the early feedback cycles and holding quality for three years mattered more than any single batch.
Where should similar work go next?
Use Multimedia services for the delivery model, the case studies hub for buyer-side evaluation, and the contact page for a scoped brief.
Similar brief
Send the constraint behind the metric.
A useful follow-up to a case study names the language mix, review model, deadline, and what proof your buyer team needs before approval.
Production-ready brief
01Closest matching challenge from this case02Language pair, dialect, and script coverage03Volume, cadence, or hours to deliver04Reviewer model and acceptance criteria05Security or platform constraints06Proof needed for stakeholder approvalCapability at a glance
The answers most briefs open by asking for.
Buyers rarely start with who we are. They start with a list of fields to fill. Here are ours, so the first email can be about the work instead.
- Languages and locales
- 300+ languages and 4,500+ dialects, quoted per locale rather than per language — because the dialect decides whether a dataset is usable, whether a market accepts a release, and which specialist the work goes to.
- Specialist network
- 110,000+ verified language specialists — linguists, annotators, and reviewers — plus voice talent and subtitlers, matched to the language, domain and task before assignment.
- Capacity and mobilisation
- Named availability confirmed per pair before scoping. Coverage is reported as staffed today or needing a recruitment window, in writing, before a launch date or release window is agreed.
- Sourcing constraints
- Specialists can be sourced against geographic, residency, locale and demographic requirements — including native-only, in-country, and speaker-diversity quotas where a data programme demands them.
- Deliverables and specs
- Work is delivered to the receiving specification: structured formats and schemas for data and annotation work, and timed-text, audio and platform conformance for media — subtitle reading speed, line limits, cue timing, channel and sample-rate requirements included.
- Comparable work
- 62 documented case studies stating the scope, the constraint that made it difficult, and the measured result — across AI data programmes, partner overflow, and media releases. 2,000+ AI projects delivered and 1,000+ brands served since 2015.
- Certifications
- ISO 9001:2015 quality management, ISO 27001:2022 information security, and ISO 17100 translation services — scoped to translation specifically, and stated that way rather than implied across every line.
- Commercial basis
- Quoted in the unit the work is measured in — per word, per audio hour, per approved hour, per finished minute, per batch, per item — with what the unit includes stated alongside it, whether the quote is for you or for a client you quote onward.
Need this against your own template? Convert your scope between units and check the deadline, then send the brief with your language list, content type, volume and deadline, and the acceptance criteria you will judge the output against — those four decide feasibility, and the reply addresses them directly.