If you translate for a living, speed only matters when it reduces post-editing. This guide shows how to integrate Lara Translate with Matecat so you get context-aware machine translation suggestions directly inside your CAT editor, while keeping full control over every segment.
In practice: you add Lara Translate as an MT engine in Matecat, paste your Access Key credentials, and start translating from a better first draft.
Short answer
In Matecat, go to Machine Translation → Add an MT Engine → select Lara, then paste your Access Key ID and Access Key Secret. Lara Translate will appear as MT suggestions inside the editor.
|
TL;DR
|
Why it matters
Matecat is where translators make quality decisions, segment by segment. When your MT engine produces drafts that miss tone or terminology, you lose time to mechanical fixes. With Lara Translate inside Matecat, you keep your CAT workflow intact and post-edit less, because the first draft is designed to behave better with context and ambiguity.
Why this integration matters for professional translators
Most MT engines are fast. The real question is whether they reduce effort or create more work. If suggestions miss tone, break terminology, or force heavy rewrites, you lose time and consistency.
With Lara Translate in Matecat, you can use AI where it helps most: speeding up repetitive segments, improving first drafts, and maintaining consistency across long projects, without leaving the editor.
What you get with Lara Translate inside Matecat
- Context-aware suggestions
Lara Translate is designed to handle context, tone, and style, so output is closer to how a professional would phrase it in real use. - Terminology consistency
Better consistency is especially useful on UI strings, product content, and recurring client language where small drift creates big rework. - Workflow fit
No exporting and re-importing. Lara Translate works where you already translate, review, and deliver. - Translator control
You decide what to accept, what to edit, and what to rewrite. Lara Translate speeds up the draft, you own the final output.
1-minute decision table: should you enable Lara Translate in Matecat?
| If you are doing this… | Enable Lara Translate when… |
| High-volume, repetitive content | You want faster drafts with less mechanical post-editing. |
| Brand or product terminology | You need more consistent suggestions across a whole project. |
| UI, app, and software strings | You care about tone and microcopy quality, not just literal accuracy. |
| Mixed source quality | You want an engine that handles context and ambiguity better, while still letting you steer the final line. |
How Lara Translate fits into the Matecat workflow
Once enabled, Lara Translate behaves like a machine translation provider in Matecat. It generates suggestions directly in the editor, so you can work in your usual loop:
- Translate: start from an AI draft instead of a blank segment.
- Edit: adjust tone, terminology, and syntax in the same place where you handle tags and formatting.
- Deliver: export with confidence, knowing output was produced and refined inside your CAT environment.
Tip for better results: keep at least one private Translation Memory active in each project. A private TM helps you reuse approved translations, reduces repeated fixes, and improves consistency when the same phrasing appears across files or releases.
Set it up in 2 minutes
If you want to test a context-aware MT engine in your CAT workflow, enable Lara Translate in Matecat and run it on a real client file. You will see suggestions per segment, right where you post-edit.
How to integrate Lara Translate with Matecat
Watch the full video:
Step-by-step setup
- Open Machine Translation settings
In Matecat, go to the Machine Translation tab and click Add an MT Engine. - Select Lara
Choose Lara from the list of available machine translation providers. - Paste your credentials
Enter your Access Key ID and Access Key Secret to connect your Lara Translate account. - Confirm your languages
Select source and target languages for your project, then save. - Translate as you go
Lara Translate suggestions will appear in the Matecat editor, ready for you to accept, edit, or rewrite.
The goal is simple: faster throughput, fewer repetitive edits, and a smoother CAT workflow where quality stays in your hands.
Quick troubleshooting
- Lara does not appear in the MT list: refresh the page, then go back to Machine Translation and click Add an MT Engine again.
- No suggestions in the editor: confirm the project language pair matches what you selected in the MT settings, and verify your Access Key ID and Access Key Secret were pasted correctly.
- Quality feels inconsistent: make sure you have a private TM active and keep terminology stable across the project, especially for product names and UI labels.
👉 Read the technical setup guide for Lara Translate in Matecat
👉 Need the Matecat-side documentation? See the Matecat guide: Lara in Matecat
FAQ
Is this the same as adding any other Matecat MT engine?
Yes. Lara Translate behaves like an MT provider inside Matecat: it returns a suggestion per segment, and you post-edit as usual.
What do I need to connect Lara Translate to Matecat?
Your Access Key ID and Access Key Secret. Paste them in the Lara engine setup panel inside Matecat.
Can I still work with tags and formatting normally?
Yes. You keep the Matecat editing environment and refine suggestions where you already manage tags, punctuation, and consistency.
What is the best way to improve consistency across a long project?
Use a private TM and keep key terminology stable. Approved terms repeated across files are where you save the most time.
Is this useful for UI and software strings?
Yes. If you care about tone and microcopy quality, context-aware suggestions can reduce the amount of rewriting compared to generic MT output.
Try Lara Translate in Matecat
Enable Lara Translate in your next Matecat project and test it on real segments. If it cuts repetitive edits while keeping tone and terminology closer to your target style, it is a keeper.
This article is about:
- How to integrate Lara Translate with Matecat as a machine translation engine.
- What you gain in a real CAT workflow: better drafts, less repetitive post-editing, and stronger consistency.
- Practical tips to improve results with private TMs, terminology discipline, and fast troubleshooting.
