Your translation pipeline is choosing between "fast but wrong" and "correct but slow." There's a third path.
Flixu analyzes your document, enforces your glossary, and applies your brand voice — before translating a single word. Your German product page sounds like you wrote it in German. At the speed of an API call.
Active · 22+ languages · Format-preserving export
Flixu is a context-aware AI translation workspace. Before translating a single word, it scans your document to detect domain, formality, and target audience — then applies your corporate glossary and brand voice rules. The result: consistent, terminology-correct translations across 22+ languages, without manual review cycles.
The B2B localization market has left a gap that neither extreme fills.
For the last decade, growing SaaS companies have been forced into the same difficult choice. Route your strings through generic AI APIs that ignore your corporate vocabulary — or integrate a legacy enterprise platform that blocks your CI/CD pipeline for months. Both cost more than they return. According to CSA Research, 76% of software buyers prefer to use products in their native language, yet most mid-market teams can't afford the tools that would actually deliver that experience correctly.
Raw AI APIs
Fast and cheap, but completely context-blind. They don't know your product, your terminology, or your tone.
- ✕ Glossary rules ignored on every string
- ✕ Output tone is generic and unpredictable
- ✕ No memory of what was approved before
Stateful Intelligence
The speed of an API call, combined with the precision of a trained linguist who actually knows your product.
- ✓ 5-dimension context analysis before translation
- ✓ Programmable brand voice, enforced automatically
- ✓ Git-native: translates and commits within your existing workflow
Legacy Enterprise TMS
Precise quality control — but buried under agency onboarding, bureaucratic review cycles, and opaque per-word pricing.
- ✕ 6–9 month integration projects
- ✕ Blocks CI/CD release velocity
- ✕ Priced for procurement teams, not product teams
What teams say after the first project.
"Awaiting real beta tester feedback on glossary enforcement..."
"Awaiting real beta tester feedback on translation memory and sprint velocity..."
"Awaiting real beta tester feedback on brand voice consistency..."
See what context-aware translation actually looks like.
Toggle between a raw, context-blind API output and the same text translated with Flixu's 5-dimension context analysis — same source string, different results.
„Wenn jemand sagt 'da liegt der Hund begraben', wissen wir, dass es um ein verborgenes Problem geht... Unser Küchenchef serviert Ihnen knuspriges Wiener Schnitzel und flaumige Marillenknödel...“
„Cuando alguien dice da liegt der Hund begraben, sabemos que hay un problema oculto... Nuestro chef les servirá un crujiente escalope vienés y esponjosas bolas de albaricoque...“
„Cuando alguien dice ahí está el meollo del asunto, sabemos que se trata de un problema oculto... Nuestro chef les servirá un crujiente Wiener Schnitzel y esponjosos Marillenknödel...“
"It wasn't built in a boardroom. I started Flixu somewhere between client calls and a spotty WiFi signal in a van on the road. I spent months switching between AI tools that were fast but completely blind to context, and human workflows that were precise but couldn't scale past three languages. The frustration was the same every time: if a translation doesn't feel like it was written for this person, in this market, it doesn't work. We built Flixu to close that gap — a quiet, precise workspace that treats language with the complexity it deserves."
How context-aware translation actually works.
What happens before the first word is translated?
Every translation in Flixu starts with a Pre-Translation Analysis. The engine reads your entire document — not sentence by sentence, but as a whole — to detect the domain (SaaS UI, legal, marketing), the intended formality level, and the target audience. Only after that analysis does it begin translating. This is what separates context-aware output from generic machine translation: the model isn't guessing. It knows where each string lives in the document.
→ See how the analysis layer works in detail: The Flixu Context EngineWhy does brand voice drift happen — and how does Flixu prevent it?
Generic APIs don't know what "your brand sounds like." They produce statistically probable translations — which is fine for informal chat, and consistently wrong for marketing copy. The Flixu Brand Voice Manager lets you define your tone once: formal or casual, warm or direct, with specific phrasing rules. That definition is injected into every translation request automatically. No briefing documents. No agency handovers. No brand voice that changes when the translator changes.
→ More on brand voice consistency in translation: Brand Voice in TranslationHow does terminology stay consistent across 22 languages?
Glossary Enforcement in Flixu is not an option you turn on — it's the foundation of every translation. Your corporate terms (product names, UI labels, legal vocabulary) are loaded before the LLM processes a single string. The result: "Dashboard" stays "Dashboard." "Cancellation" doesn't appear as three different words across your app in the same language. Teams report that automated glossary enforcement eliminates the majority of their post-translation review cycles entirely.
→ Learn how glossary management works at scale: Glossary EnforcementHow does Flixu fit into a developer workflow?
Connect Flixu to your GitHub repository. When a developer pushes new English strings, Flixu detects them, translates using your configured Translation Memory and glossaries, and commits the translated files back into a separate branch — without touching your main branch. The German, French, or Japanese version of your feature goes live when the feature does, not three weeks later. Teams who've moved from manual file uploads to Git-native workflows report their localization coordination time drops from multiple hours per sprint to under 30 minutes.
→ GitHub App and CI/CD workflow details: GitHub IntegrationWhat happens when Flixu isn't sure about a translation?
Every translated segment receives an automated LQA score across five dimensions: grammar, accuracy, terminology consistency, formatting (tags and placeholders), and fluency. If the score clears the threshold — either a 99% Translation Memory match or an LQA score above 90 — the translation is auto-approved without human review. Segments that fall below the threshold are flagged for a human reviewer with the specific reason marked. You only read the things that actually need your attention.
→ Full quality assurance workflow: LQA & Quality AssuranceFrequently Asked Questions
Does Flixu break my JSON, XLIFF, or .strings files?
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No. Flixu preserves your exact file structure and formatting on export. You can upload Markdown, JSON, XLIFF, iOS .strings, .po, .yaml, .docx, and subtitle files. The downloaded output is structurally identical to the import — every tag, every placeholder, every line break stays where it was. Your developers won't spend time fixing broken layout files.
How does Flixu know my internal product terminology?
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You upload your glossary once — product names, UI labels, legal terms, brand-specific vocabulary. From that point forward, Flixu enforces those terms on every translation request, across all 22+ supported languages. Terminology that isn't in your glossary is handled by the context analysis layer, which infers the correct register and domain from the document itself.
What's the difference between Flixu and using DeepL or Google Translate directly?
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DeepL is excellent at fast, raw translation for informal content — and if that's what you need, it's hard to beat. Flixu takes a different approach: the Context Engine runs a 5-dimension analysis before translating, which matters when glossary adherence, brand voice consistency, and terminology precision are requirements, not nice-to-haves. Flixu also retains Translation Memory across projects, so the output improves over time.
Can my human translators still review and edit the output?
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Yes. Flixu is designed as a collaborative workspace. You can invite your translators, agency contacts, or in-house reviewers at specific roles (Translator, Project Manager, Admin). When a reviewer edits a segment, the correction feeds back into the Translation Memory — so the system learns your preferences and doesn't repeat the same stylistic mistakes.
Is there a free tier?
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Yes. Flixu offers a free tier for independent translators and small teams to run their first projects. Paid plans are structured around word volume, with transparent credit-based pricing and an automated top-up option to keep pipelines running without manual intervention.
How does Flixu handle data privacy and GDPR?
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Flixu processes translation inputs ephemerally. Your documents and strings are not stored beyond the active session and are never used to train shared or public AI models. Your Translation Memory and glossary data belong to your workspace and remain private. For detailed compliance information, see the Privacy Policy.
Does Flixu adapt currencies, date formats, and measurements automatically?
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Yes. The Cultural Adaptation Engine handles non-linguistic localization automatically alongside translation — converting date formats (DD.MM.YYYY vs. MM/DD/YYYY), adapting currency symbols, switching between metric and imperial measurements, and adjusting timezone references to the target region. This is included in every translation, not an add-on.
Can Flixu connect directly to our CI/CD pipeline?
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Yes. The GitHub App handles the integration without manual file management — developers push English, translated strings come back in a separate branch. For teams with custom deployment pipelines, the Developer API supports direct integration with GitHub Actions or your existing deployment infrastructure.
Your glossary. Your brand voice. Your release schedule.