Case study
607,000 words, 17 languages.
An LSP partner needed rare-language translation, editing, and proofreading at two very different tempos: a 10-day surge, then a four-month sustained programme.
607,000 words - 17 - 5 — Latin, Bengali, Arabic, Devanagari, Cyrillic
607,000 words
Volume delivered
17
Unique languages
Measured outcomes
Rare-language TEP, two phases
Project overview
What landed, and what made it hard.
An LSP partner needed rare-language translation, editing, and proofreading at two very different tempos: a 10-day surge, then a four-month sustained programme.
Delivery snapshot
Rare-language TEP, two phases
- Client
- confidential language-service partner
- Service
- Translation, editing, proofreading
- Volume
- 607,000 words across 17 languages
- Phase 1
- 8 languages, 257,000 words, 10 days, project-scoped quality review
- Phase 2
- 12 languages, 350,000 words, 4 months, project-scoped quality review
Why this mattered
Outcome before process.
Phase 1 was compression — 8 rare languages, 4 scripts, 257,000 words, 10 calendar days. Phase 2 was endurance — 12 languages over four months, adding materially harder ones.
Across both phases the work covered 17 unique languages and 5 script systems: Latin, Bengali, Arabic, Devanagari, and Cyrillic.
MoniSa handled the work under its Triple ISO operating context: ISO 9001:2015 for process control, ISO 27001:2022 for information handling, and ISO 17100:2015 for translation-service discipline, which governs the second-review principle this work depended on.
The two phases returned different accuracy figures, and and that difference is reported rather than averaged, because it is the most informative number in the case.
The problem to solve
Why the work was difficult, and what MoniSa changed in-flight.
Phase 2 was harder than Phase 1 in a way the word counts do not show. It added Tuvanian, written in Siberian Cyrillic; Navajo, which has almost no standard translation infrastructure; and Kashmiri, which is written in two scripts.
The challenge
The problem to solve
Dual-script Kashmiri is the clearest example of why a language count understates rare-language difficulty. It is one entry on a language list and two production workflows, each needing its own QA.
Navajo carries a different problem: the professional translation infrastructure most languages take for granted — glossaries, style references, an established reviewer pool — barely exists, so the workflow has to supply what the ecosystem does not.
The 10-day Phase 1 window left no room for sequential sourcing. Eight rare languages across four scripts cannot be recruited, briefed, produced, and reviewed one after another inside two working weeks.
Five script systems means five sets of rendering, encoding, and QA requirements. A translation that is linguistically correct and breaks in its script is not delivered.
The buyer-side risk across both phases was single-point failure. In rare languages the qualified pool can be very small, and losing one linguist mid-phase can stall an entire language.
Operating response
What MoniSa changed
A pre-built rare-language bench was activated on demand rather than recruited at project start, which is the only way an 8-language, 4-script, 10-day surge is deliverable at all.
- Pre-built bench, activated The rare-language bench existed before the brief. Ten-day delivery across eight rare languages is a sourcing outcome, not a production one.
- Staggered parallel delivery Languages ran in parallel with offset delivery dates so review capacity was not all demanded at once.
- QA per script system Five scripts got five QA treatments, because rendering and encoding failures are script-specific and invisible to a combined check.
- Kashmiri as two workflows Dual-script Kashmiri was produced and reviewed separately per script rather than converted mechanically from one to the other.
Results
Measured outcomes from this engagement.
607,000 words were delivered across 17 unique languages and 5 script systems, in two phases with different tempos and different difficulty profiles.
| Volume delivered | 607,000 words |
|---|---|
| Unique languages | 17 |
| Script systems | 5 — Latin, Bengali, Arabic, Devanagari, Cyrillic |
| Phase 1 accuracy | project-scoped quality review — 8 languages, 257,000 words, 10 days |
| Phase 2 accuracy | project-scoped quality review — 12 languages, 350,000 words, 4 months |
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
The work required a rare-language bench that already existed, plus script-specific QA across five writing systems and two very different delivery tempos.
What decided the result
What decided the result
Reporting the phase-to-phase accuracy difference honestly told the partner more about future capacity than a blended figure ever could.
What buyers can reuse
What buyers can reuse
- Ask for accuracy by phase and difficulty tier, never as a project average. An average conceals the hardest languages, which are the ones you are buying the vendor for.
- A language count understates rare-language difficulty. Dual-script Kashmiri is one language and two production workflows.
- Compressed multi-language delivery is a sourcing outcome. If the bench is built after the brief lands, the date is already at risk.
- QA must run per script system. Rendering and encoding failures are script-specific and survive a combined check.
- In rare languages, ask what happens if one linguist becomes unavailable mid-phase. The qualified pool may be small enough that there is no answer.
- Zero missed deadlines over four months is a stronger signal than a high accuracy figure over ten days. Sustained delivery is the harder test.
- A useful rare-language brief names the scripts, the review standard, the per-language deadline, and the contingency for linguist unavailability.
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.
More proof
Related proof
Compare this case with Rare-language TEP sprint and Rare-language evaluation at scale to judge whether the operating pattern fits your brief.
case evidence
Nearest proof pattern.
These related cases keep the next click close to the same kind of work.
AI data services500 hours transcribed at project-scoped quality review on peer review, with accent-specific transcriber pools.
Regional-accent transcription
The challenge. A partner needed French Canadian, Russian, and Persian transcription where regional variety and technical terminology both had to hold.
What we did. MoniSa sourced by variety rather than language, deployed 15 transcribers, and ran peer review and spot checks during production.
The result. 500 hours with project-scoped quality review measured by spot-check peer review.
Recognise your own project in one of these?
Send the language list and volumeTranslation servicesChild nutrition guidance delivered in a language with roughly 34,000 speakers worldwide.
Pohnpeian child nutrition
Problem. An LSP partner needed Pohnpeian health content where the qualified translator pool is countable and no standardized health terminology exists.
Action. MoniSa sourced through its specialist network and made terminology decisions judged on reader comprehension.
Result. 20,000 words delivered — reach into a language few suppliers can source at all.
Translation servicesEnglish–Uyghur delivered and accepted in a pair the localization market barely staffs.
Uyghur, a scarce pair
Problem. An LSP partner needed a scarce language pair where availability, not quality, is the dominant delivery constraint.
Action. MoniSa sourced through its specialist network and delivered against the partner's own acceptance standard.
Result. 20,000 words delivered within partner quality standards.
Buyer questions
Answers in writing, before you ask for a call.
The questions buyers send before a scope conversation, answered on the page rather than in a meeting. Take them to your team, then send us the one we did not answer.
What was delivered on this engagement?
Volume delivered: 607,000 words. Unique languages: 17. Script systems: 5 — Latin, Bengali, Arabic, Devanagari, Cyrillic
What control kept the work stable?
Reporting the phase-to-phase accuracy difference honestly told the partner more about future capacity than a blended figure ever could.
Where should similar work go next?
Use Translation services for the delivery model, Rare-language translation buyer guide for buyer-side evaluation, and the contact page for a scoped brief.
What happens if you cannot staff one of my language pairs?
You are told before a date is agreed, not after. Coverage is reported pair by pair as staffed today or needing a recruitment window, with the window stated — in writing, while the scope is still being agreed. Nobody new goes onto live work until a pilot batch has been reviewed and signed off. A coverage claim you cannot check before signing is not coverage.
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 approval