AI by industry

AI for translation agencies in Portugal

Machine translation is the least interesting AI decision a translation agency makes this year. The margin is in everything that happens before and after the linguist.

Agencies in Lisbon and Porto are not losing hours to translating. They are losing hours to counting words in a PDF a client sent as a photo, to chasing a freelancer who has gone quiet on a Friday, and to rebuilding a glossary that already existed in a file nobody could find. Those are automation problems, and they respond well.

Quoting, which is where the day goes

A quote request arrives as an email with four attachments in three formats. The repeatable work is extraction, then word and repetition counting against the client's translation memory, then applying the right rate card, then producing a quote in the client's language. An agent can do the extraction and the counting reliably, including scanned documents through OCR, and produce a draft quote with the match bands broken out. Keep the final number under human eyes. The point is that a quote takes four minutes instead of forty.

Glossary and translation memory hygiene

Every agency has termbases that decay. Retrieval over your own TMX and glossary files, rather than a general model guessing, is the single change that most improves consistency. Practical uses:

• Flag segments in a delivered file where the linguist used a term that contradicts the client glossary, with the segment ID and the approved term.
• Propose new glossary candidates from repeated untranslated terms across a client's last twenty jobs.
• Answer a linguist mid-job: how did we render this term for this client in 2024, and where.

Vendor allocation and chasing

Matching a job to a linguist is a scoring problem with rules you already apply informally: language pair, specialism, past QA scores for that client, current load, rate, and whether they answered last time. Encode it. Then let an agent handle the follow-up sequence when a purchase order is unacknowledged after a set number of hours, escalating to a human before the deadline gets tight rather than after.

QA that runs before delivery

Automated checks catch the errors that generate credit notes: number and date mismatches between source and target, untranslated segments, inconsistent product names, missing tags, wrong locale conventions. Run them on every file, log the result, and give the client a QA summary. That log becomes useful evidence when a complaint arrives six months later.

Certified and sworn work stays manual for a reason

Certified translation in Portugal runs through a notary, a lawyer, a solicitador, or a consulate, and the apostille process on top of it. Automate the admin around it, the checklist, the document tracking, the client status updates, and leave the attestation exactly where the law puts it. The same rule applies to anything a court will read.

Where to start

Pick the process that generates the most unbilled hours, usually quoting, and instrument it first. Digiton builds and operates this kind of workflow from Lisbon, in English, Portuguese and French. A short AI audit will tell you which of the five above is worth building for your volume.

Frequently asked questions

Related