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From fax machines to AI — and we were there for all of it.
The translation industry has gone through more technological disruption in 23 years than in the previous century. We have not just observed these changes — we have adapted to each one, integrated what worked, and built our own workflows around what serves clients best.
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More than a vendor. A language partner.
Every program starts with the right people. We assemble a core team around your content type: a lead translator and editor, a subject-matter reviewer, a project manager, a DTP specialist, and a quality lead. Overflow linguists and a Human-in-the-Loop reviewer are added for peak volumes and deadline-critical work.
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▮The Fax Era — 2002 Alafranga was founded in 2002 — at the tail end of the fax machine era. Documents crossed borders by fax. Poor transmission quality meant manual retyping. Retyping meant errors. The translator's first job was often to reconstruct the source text before translating it.
This is where our attention to source document integrity began — a discipline that has carried through every technological shift since.
▮The CAT Tool Revolution Computer-assisted translation tools changed everything. Translation memory — storing approved segments for reuse across a project — eliminated the most wasteful part of translation: retranslating identical or near-identical content.
We work natively in MemoQ and SDL Trados. Client-specific translation memories and glossaries are built from the first project and maintained across every subsequent one. The longer the relationship, the faster and more consistent each project becomes. What CAT tools also introduced: accountability. Every segment has a history. Every decision is traceable. Every revision is logged.
▮Smartcat — Collaborative Project Infrastructure For large projects requiring multiple translators working simultaneously, we use Smartcat as our collaborative project environment.
Every translator on the project is connected to the same shared translation memory in real time. An approved segment written by one translator is immediately available to all others — preventing duplication, eliminating inconsistency, and maintaining terminology governance across the entire team.
For clients with in-house domain expertise: Engineers, legal teams, and medical professionals can contribute directly to the shared translation memory. When your specialists define how a term should be translated — a product name, a regulatory concept, a brand-specific expression — that decision is written to the shared TM and applied automatically across all translators and all future projects. Your institutional knowledge becomes part of the translation infrastructure. Smartcat also gives project managers a real-time view of task progress, reviewer assignments, and delivery status across all language pairs and team members — without email chains or manual status updates.
▮The AI Integration — SmartEdit The integration of AI into translation workflows is the most significant shift since CAT tools — and the most misunderstood.
AI translation tools promise speed and cost reduction. Most deliver on speed. Fewer are honest about what happens when the AI gets terminology wrong, misreads context, or produces fluent but inaccurate output.
At Alafranga, AI is not a replacement for professional translation. It is a controlled production layer — with human expertise at every critical checkpoint. We call this SmartEdit.
Three AI engines in our workflow:
- GPT — for general and narrative content
- Claude — for technical and structured content
- DeepL — for high-fluency European language pairs
Your translation memory and glossary are enforced before the first segment is generated. Every AI output is reviewed and signed off by a named human specialist before delivery. We do not send unreviewed AI output to clients.
SmartEdit Pro adds an independent second reviewer after post-editing — for customer-facing content, regulated materials, and complex technical documentation where dual human review is required.
▮What Has Not Changed Technology changes the speed, the format, and the toolchain. It has not changed what good translation requires:
- A specialist who understands the subject matter
- A reviewer who checks against the source independently
- A project manager who knows the client's context
- A quality framework that holds all three accountable
These four elements have been constant since 2002. The tools around them have evolved. The discipline behind them has not.