Case study
Five months of continuous healthcare SaaS localization.
A healthcare SaaS platform needed its product content localized into Hindi as a continuous, months-long program, where a single quality slip in healthcare content carries real consequences.
Hindi - 100,000 words - 5 continuous months
100,000 words
Volume
5 continuous months
Duration
Measured outcomes
Healthcare SaaS localization
Project overview
What landed, and what made it hard.
A healthcare SaaS platform needed its product content localized into Hindi as a continuous, months-long program rather than a one-time batch.
Delivery snapshot
Healthcare SaaS localization
- Client
- confidential healthcare SaaS platform (via a localization platform partner)
- Service
- Continuous content localization
- Language
- Hindi
- Engagement
- 5 continuous months
Why this mattered
Outcome before process.
Healthcare content leaves little room for drift: terminology and tone have to stay exact and consistent across every release for five straight months.
The problem to solve
Why the work was difficult, and what MoniSa changed in-flight.
Healthcare-adjacent content raises the cost of any quality slip, so the work needed steady accuracy rather than a strong first batch followed by drift.
The challenge
The problem to solve
A continuous five-month cadence meant the same reviewers had to hold terminology and tone consistent release after release, not re-learn the account each month.
Operating response
What MoniSa changed
MoniSa ran the account with a steady reviewer team and a fixed terminology base, treating consistency over time as the core deliverable.
- Steady reviewer team The same linguists stayed on the account across the five months, holding tone and terminology stable.
- Fixed terminology base A shared glossary kept healthcare and product terms consistent from one release to the next.
- Continuous quality watch Each batch was checked against the prior ones, so consistency was monitored, not assumed.
Results
Measured outcomes from this engagement.
The platform received 100,000 words of localized healthcare SaaS content across five continuous months with quality issues stayed inside the agreed review path.
| Language | Hindi |
|---|---|
| Volume | 100,000 words |
| Duration | 5 continuous months |
| Quality | quality issues stayed inside the agreed review path across the engagement |
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
A healthcare-adjacent program rewards consistency over months, which a steady reviewer team provides better than a rotating pool.
What decided the result
What decided the result
Holding the same reviewers and glossary is what kept tone and terminology stable across a five-month cadence.
What buyers can reuse
What buyers can reuse
- In healthcare-adjacent content, consistency over time matters as much as any single batch score.
- A steady reviewer team and a fixed glossary kept quality level across five continuous months.
- The evidence keeps the client 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.
- Hindi
- Healthcare content localization
- Continuous monthly delivery
More proof
Related proof
Compare this case with Six years of app localization and Cultural adaptation across indigenous languages to judge whether the operating pattern fits your brief.
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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?
Language: Hindi. Volume: 100,000 words. Duration: 5 continuous months
What control kept the work stable?
Holding the same reviewers and glossary is what kept tone and terminology stable across a five-month cadence.
Where should similar work go next?
Use Localization services for the delivery model, Translation vendor buyer guide 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.