230+ Languages & 10,000+ Projects Delivered

Go Global — We Help You Sound Local.

With more than 15+ years of experience, a network of 8,000+ expert linguists & data collectors, and coverage of 230+ languages, we help businesses transcend borders.

230+

Languages

10,000+

Projects

8,000+

Linguists

500+

Clients

Trusted by global enterprises

Partner logo
NHS logo
Zoho logo
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Brands Worldwide Trust Saytica

From startups to enterprises, we deliver native-quality content in 230+ languages — on time and on budget.

Join the 500+ companies who trust Saytica.

Global Team Collaboration
About Us

Our journey in Localization, media and AI data

With decades of experience, we help global businesses adapt their content across languages and cultures with accuracy and impact. Our commitment to excellence drives every project we undertake.

230+
Languages
10,000+
Projects delivered
15+
Years
8,000+
Linguists & Annotators

How we work

Scope & sample

Tell us your target quality and we'll run a free sample.

Pilot & calibrate

Micro guides, glossary, and a short pilot to lock the bar.

Production

Parallel lanes and vendor routing for speed and cost.

QA & governance

Gold sets, IAA, scorecards and changelogs.

Deliver & integrate

Files in your format, with docs and handover.

Iterate

TM updates, MT tuning, or dataset expansion as needed.

Built on modern tools & secure processes

Trados
memoQ
Phrase
Smartcat
Figma
InDesign
Subtitle Edit
Pro Tools
Label Studio
CVAT
AWS S3
GCP
Azure
GitHub
GitLab
Jira
Kaltura
Vimeo
YouTube

Logos indicate compatibility, not endorsement. Custom integrations available via API/webhooks.

Security & privacy

NDA on request

TLS & AES-256 encryption

Role-based access

Consent artifacts for dataset projects

In-tenant deployment available

Audit logging

Testimonials

What Our Partners Say

From product UI to dubbing to AI training data, here’s what partners say about working with us.

Eamonn Gorman
Head of Clinical Informatics at NHS England

Accurate transcripts with PII handled correctly. Reliable, secure, and easy to work with. Diarization, timestamping, and redaction were consistent across large volumes. Their process fit neatly into our clinical workflows. 

Client Success Stories

Discover how we helped businesses achieve their global communication goals

We had three vendors, four project managers across our side, and a 5-day TAT that was breaking our release cycle. Eight months in, we have one pipeline, one point of contact, and turnaround that actually matches how we ship. The bigger shift was internal. My team stopped doing localization project management and started doing localization strategy.
A. Vasiliev
CTO
B2B SaaS Platform (NDA, Europe) logo

Challenge

The client is a B2B SaaS platform headquartered in Europe, serving customers across 25 markets. Their product ships continuously, two-week sprints, sometimes hot-fixes mid-sprint, and every sprint introduces around 3,000 new or modified strings across UI, in-app help, email templates, and onboarding flows.When they came to us, the localization setup was a patchwork. One agency handled European languages, another covered APAC, and a third did MENA. Each vendor had its own project manager, its own quote format, its own quality issues, and its own delivery schedule. The average turnaround from a developer committing a new string to that string appearing in all 25 languages was five days. For a team trying to ship weekly, that was a release blocker.The bigger problem was sprint adherence. Roughly 1 in 6 sprints either shipped with missing translations (English fallback visible in production), or got delayed because the localization deliverables hadn't arrived. Their Head of Globalization was spending most of her time chasing vendor status emails instead of working on strategy.They had tried building an internal localization team. It worked for about a year and then scaling stalled. Hiring senior linguists in 25 languages out of one European office wasn't realistic, and the contractor pool they were assembling was expensive and inconsistent.

Solution

The first conversation wasn't about translation. It was about their dev workflow. We spent the first two weeks just understanding how they shipped product. Which TMS they used (Phrase), how their CI/CD pipeline was structured, where strings lived in their repo, how their PMs flagged content for translation, and what their definition of "done" was for a localized release.The core decision was to stop treating localization as a separate workflow. We integrated directly into their Phrase instance through API, set up webhooks for new content, and built a routing layer that automatically assigned incoming strings to the right language pod based on content type and priority tag.We restructured the linguist side too. Twenty-five language pods, each with a senior translator and a reviewer. Each pod was on-call during their regional business hours, which meant strings committed by the dev team in Berlin at 10 AM were typically being worked on within an hour, with Asian languages picked up overnight and European languages handled same-day.The QA layer was the part that took longest to get right. SaaS strings have specific risks that document translation doesn't (character limits in UI elements, ICU MessageFormat placeholders, plural rules, gendered grammar in form labels). We built an automated QA layer that ran every translated string through validation checks before it went back to the client's TMS, catching things like broken placeholders or strings that would overflow buttons in German or Russian. Anything that failed automated checks went to the reviewer with a flag.We also rebuilt their translation memory. The three previous vendors each had their own TM, with overlapping entries, conflicting terminology, and roughly 35% leverage on average. After three months of consolidation and cleanup, TM leverage was up to 62%, which translated directly into lower cost per word and faster turnaround on familiar content.The integration engineering work, two of our engineers worked with the client's platform team for the first six weeks, was probably the highest-leverage investment. Once the pipeline was running, manual intervention dropped to almost zero. Strings flow in, get translated, get QA-checked, and flow back into the right branch without anyone emailing anyone.By month three, the 5-day TAT was 18 hours. By month six, sprint adherence was at 99.7%. The Head of Globalization had stopped chasing status emails.

TAT 5 days to 18 hours, 3 vendors consolidated, 99.7% sprint adherence
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Our incumbent quoted 14 weeks for 28 languages. Saytica delivered 40 in 6, including ones we'd been told weren't possible. What surprised me more was the evaluation work. Three jailbreaks in low-resource languages caught before they reached production. Honestly, that's not work we knew to ask for.
M. Chen
Head of Localization
Conversational AI Platform (NDA, North America) logo

Challenge

The client is a North American conversational AI company. Their Series B closed in early 2026, and the lead investor wanted international expansion fast, before two well-funded competitors got there. The board signed off on a target: 40 languages in 8 weeks, covering EMEA, APAC, and LATAM. Their internal localization team was two people. The incumbent LSP, a tier-1 agency they'd used for marketing translation, came back with a 14-week timeline and a list of 28 languages they could confidently deliver. The remaining 12, including Sylheti, Khmer, Amharic, Pashto, Burmese, and Tigrinya, were either declined or quoted at premium rates with no quality guarantee. The harder problem showed up in beta testing. Machine-translated system prompts made the assistant feel cold in Japanese, oddly formal in Brazilian Portuguese, and culturally off in three other markets. Refusal templates, the "I can't help with that" messages, translated literally and came out rude in Japanese and excessively apologetic in German. None of this was anyone's fault exactly. It just wasn't work their LSP knew how to do.

Solution

We started with a hard look at the workflow. The standard agency pattern, translate then review then QA in sequence, was never going to hit six weeks for forty languages. So we ran them all in parallel. Forty language pods, each with a senior translator, a reviewer, and an AI-context specialist (usually a linguist with prompt engineering or model evaluation experience). Product surface work, UI strings, help docs, marketing pages, error messages, ran continuously and synced to the client's repo daily through API. This part most modern LSPs can do. The behavior layer was where the actual work happened. We didn't translate system prompts word-for-word. The Japanese pod rewrote the assistant's default formality level because neutral keigo is technically polite but lands as distant. The Brazilian Portuguese pod swapped formal "você" patterns for warmer regional phrasing in onboarding. The Arabic pod sorted out gender agreement and RTL UI rendering together, because the assistant's text was breaking visually in mixed-language conversations and nobody had flagged it. For evaluation, each pod ran a 500-conversation test set scored by native raters on a 5-point rubric covering naturalness, cultural fit, and safety behavior. The MT baseline averaged 3.1 across languages. Our localized output averaged 4.6. More importantly, three jailbreak prompts that bypassed safety in machine-translated Bengali, Pashto, and Burmese got caught and patched before launch. Those weren't on anyone's deliverable list. They were things our linguists noticed and flagged. The 12 languages the incumbent declined went to our in-country specialist network. Native Sylheti reviewers in Sylhet. Amharic linguists in Addis Ababa. Pashto speakers in Peshawar. Vetted teams with credentials we can vouch for, not freelancer marketplace work. All 40 languages delivered in six weeks, two weeks ahead of the client's deadline.

40 languages in 6 weeks, 38% under incumbent quote
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The subtitles were perfectly timed and flawlessly accurate. Your attention to detail and understanding of our brand voice made the video far more engaging and accessible. We were impressed by the quick turnaround and professional quality — a fantastic experience working with you!
Paul Grimes
Chief Operating Officer
Zoho logo

Challenge

Make videos accessible and on-brand across markets without slowing publishing.

Solution

Style-guided spotting with read-speed and line-break control, SDH compliance, and review previews; delivered platform-ready SRT/WebVTT for immediate upload.

23% increased, expanded in 2 regions
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Saytica's vetting and studio model gave us confidence quality would hold at scale. They delivered twelve days early without a single escalation — exactly what we needed for production-grade voice AI.
Tsumugi
Project Lead, Voice AI Programme
Renesas logo

Challenge

Build a production-grade Hebrew and Arabic voice command dataset for an automotive voice AI system in 45 days.

Solution

We ran a three-stage linguist vetting funnel to assemble a 70-artist talent pool across 5 dedicated studios, with two in-house teams running 24/7 coverage and a 22-person multi-pass transcription pipeline.

2,000+ Voice Commands · 12 Days Early
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The team delivered exceptional results under tight timelines. The dataset quality, diversity, and compliance were beyond expectations — all while staying well within budget. Their structured approach to consent, auditing, and documentation made this one of our smoothest AI data projects to date.
Maria Thompson
Project Lead
DataOceanAI  logo

Challenge

Build a diverse, consented dataset of real-person images across six races—fast and within budget.

Solution

We activated our worldwide vendor network, issued clear consent + capture guidelines, ran duplicate/quality checks, and labeled to spec with gold-set audits and documentation.

63% Cheaper, 70% Faster
Read case study
Slide 1 of 5: B2B SaaS Platform (NDA, Europe)

Languages — global coverage

We support 230+ globally relevant languages across every region.

    Asia & Central Asia

    68 languages

    Middle East & North Africa (MENA)

    28 languages

    Sub-Saharan Africa

    45 languages

    Europe

    52 languages

    The Americas

    25 languages

    Oceania & Pacific

    18 languages

    Global / Constructed / Other

    10 languages