We built a multilingual AI translation workspace that combines a live termbase, AI-assisted suggestions, fuzzy search, and real-time terminology validation to support professional translators. The platform improved translation turnaround by 73%, achieved 92% linguist-accepted accuracy, and reduced manual QA effort by 57%
A US-based language technology company serving professional translators and language service providers needed to improve terminology consistency across large multilingual projects. Its termbase contained more than 250,000 globally managed entries across 50+ languages and was used by 200+ active professional translators.
Ciphernutz built a multilingual terminology management and AI translation platform that brings approved terminology directly into the translation workflow. The platform combines real-time termbase validation, AI-assisted suggestions, fuzzy search, role-based permissions, keyboard-optimized UX, and REST APIs for integration with professional CAT tools.
"What did your translators say the first time they used the AI suggestions?"
Our biggest fear was that an AI tool would frustrate our senior linguists by trying to override their expertise or breaking their flow. Instead, the platform acts like a brilliant co-pilot that hands them the exact approved terminology they need, right when they need it. Because the translator always retains final control over the segment, adoption was completely frictionless. It hasn’t replaced our team; it has given them superpowers.
Professional translation at scale is not only a language problem; it is a consistency problem. Multiple translators working across thousands of segments need to use client-approved terminology consistently, especially for technical and regulated content.
Approved terminology was maintained in termbases that could be difficult to consult while translating. Translators working under deadline could miss terminology requirements, causing inconsistent output and increasing downstream QA effort.
AI suggestions had to support professional translators rather than replace their judgment. Suggestions needed to be context-aware, genuinely useful, and always overridable. The system also needed to protect confidential client termbases through granular permissions.
AI had to support translators, not replace their judgment. Suggestions needed to be useful, with translators always in control.
Linguistic search had to handle misspellings, variations, and synonyms while returning results instantly.
Termbases contain confidential client data, so permissions had to keep each client’s terminology strictly separated by user and termbase.
We engineered a high-performance multilingual translation workspace that makes terminology management an active part of the translation process. Approved terminology is validated and surfaced inline while translators retain final control over every segment.
The platform manages multilingual entries with contextual metadata and real-time validation. AI provides live suggestions, inline terminology enforcement, and quality feedback while allowing the translator to make the final decision on every segment.
Live suggestions, inline terminology enforcement and real-time quality feedback - with the translator retaining final say on every segment. The enforcement is the important half: approved terminology surfaces at the moment of translating rather than in a document the translator has to remember to open. Consistency stopped depending on discipline and became a property of the workspace.
High-performance search with fuzzy matching, multi-criteria filters and synonym handling. It tolerates the misspellings and inflections that real linguistic queries contain, and returns fast enough not to interrupt work.
Granular permissions control access per termbase, so a provider serving competing clients keeps their terminology assets properly separated.
Vue.js and TailwindCSS, built for speed and full keyboard navigation. This is not a cosmetic detail - professional translators work at pace and measure tools by whether they can stay on the keyboard. Forcing a hand to the mouse per segment costs real throughput.
Endpoints connect to CAT tools, enterprise translation systems and third-party linguistic databases, so the platform fits existing workflows rather than requiring translators to abandon tools they already use.
Translation turnaround improved 73%, terminology consistency increased 68%, manual QA effort fell 57%, and the platform achieved 92% accuracy accepted by linguists. The termbase evolved from a reference document into a live, searchable, permission-controlled part of the translation workspace.
| Before | After | |
|---|---|---|
| Terminology Consistency | Dependent on translator memory | Enforced inline |
| Search | Exact match, slow | Fuzzy, synonym-aware, instant |
| Termbase | Spreadsheet, consulted occasionally | Live, enforced in the workspace |
| Errors | Caught in QA, late | Prevented at translation |
| Client Separation | Manual discipline | Role-based permissions |
We design AI assistance that professionals can trust. Let us design you an AI workflow that improves your productivity and consistency.
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