Local AI for technical translation agencies

Syntalith proposes an integration where translators work with the source text, approved project terminology and a model's draft, then transfer their reviewed version into their translation tool. The scope can build on the team's existing computer-assisted translation (CAT) environment. Before commissioning it, compare that workflow with the features the agency already has.

“Housing” in two projects

Suppose an agency is translating into Polish. Client A's approved glossary gives “obudowa” as the translation of “housing.” For client B's project, “korpus” is approved in the context described by that glossary. The model drafts text for B using “obudowa.” The sentence reads naturally, but the translator has to revise it to match the project's resources.

In the proposed review view, the translator can see which project the passage belongs to and open the relevant terminology entry beside the source and draft. They check the context, change the term and approve the text for further work. The model supplies a suggestion; the people reviewing the translation assess its technical accuracy. If the glossary does not resolve that particular use, the question goes to the person responsible for terminology.

Start with the translation memory and term base

A translation memory stores earlier translations for reuse. A term base holds agreed equivalents for words and phrases. memoQ's documentation describes using both resources during translation.

If revisions stem from a project using the wrong term base, or approved changes never reaching the team's resources, address that workflow in CAT first. Adding a model will leave the problem in place for the next assignment. Existing memory matches and terminology suggestions may be enough for recurring passages.

Local AI is worth considering for passages that need fresh wording or revision, where a translator wants a draft informed by the client's resources. Switching projects can mean selecting the appropriate materials for the application. It does not automatically require a separately fine-tuned model for each client.

Where the text goes during translation

Suppose a client has approved text processing only within a specified agency environment. A local model can run on a computer or server there. Its location alone, however, does not describe the document's path through the entire application.

The integration needs to account for where files and saved drafts remain, and whether records of application activity contain excerpts. A CAT plugin or an additional service may send content outside that environment.

The person responsible for IT compares the actual data flow with the agreed project requirements. They establish access to the materials and how to handle support requests that require someone to view the text. Those arrangements also cover later updates to the integration.

Do the suggestions help translators?

The comparison should cover the language pair and documents the team actually works with. Translators assess how much revision a suggestion needs, whether it preserves the source meaning and whether it uses the right client's terminology. Waiting time on the intended equipment and moving text between windows also count. A sentence that takes less editing may not make up for an awkward workflow across the whole assignment.

The agency can compare this with its current translation workflow in CAT. Reviewed suggestions and translator feedback, including rejected drafts, provide a basis for the decision. They help establish which materials the integration suits and what still needs work before wider use.

Proposed scope for a translation agency

Through its AI application work, Syntalith can build a local workspace connected to client resources and an agreed way to transfer reviewed text into CAT. An initial scope could cover one language pair, connections to available project resources and a view for comparing the source with the draft. The integration approach depends on the capabilities of the existing software and the permitted data flow.

The agency's team identifies recurring corrections and the person who will review translations and approve terminology resources. Together, we agree on material for a trial, the working environment and ongoing maintenance of the CAT connection. Before expanding the scope, the team can examine suggestions in the context of translators' daily work.

Tell us about a terminology correction that keeps returning, the CAT tool you use and where text processing is allowed. That is enough to begin a conversation without sharing confidential documents. See our pricing page for information about estimates.