Your team's intent,
not a string database
Translation Memory is a rigid database that blindly memorizes the past — including all your old mistakes — and effectively forces you to repeat them forever. Living Memory is different.
Traditional Translation Memory
- Matches strings
- Stores outputs, not intent
- No concept of audience and register
- Gets worse over time as matches increase
Living Memory
- Learns from context
- Encodes the team's voice
- Audience is part of every suggestion
- Gets better and more precise as the project grows
Your Translation Memory is faithfully preserving your mistakes
Translation Memory was designed as a productivity tool — store a translated segment once, reuse it forever. It works great for identical strings in software UIs. For anything richer, it's a liability.
TM knows what you translated years ago. It has absolutely no concept of why. Every imprecise choice, every outdated terminology decision, every mistake your team made in 2019 is still being faithfully injected into your 2024 translations.
And as your TM grows, the problem compounds. More entries means more conflicts, more noise, and more pressure to accept suggestions that don't quite fit — because rejecting them adds overhead.
"Reviewing AI translations often costs more than translating from scratch — because correcting something broken is harder than building something right."
The same principle applies to TM: the more you've locked in, the harder it is to change course.
Translation Memory vs Living Memory
Hover any row to learn more
How it works
Your past choices, working for you
Every time you focus on a passage, Living Memory finds relevant decisions from your own project and uses them to draft a suggestion. The result sounds like your team, because it's built from your team's choices.
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You focus on a passage.
Living Memory activates the moment you do.
"And what is the use of a book," thought Alice, "without pictures or conversation?"… -
Your project is searched by meaning.
Every past decision is compared — not by words, but by what they mean.
Searching…
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Relevant passages surface.
The closest moments from your own work rise to the top.
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Your past choices become context.
The AI sees how your team has handled situations like this before.
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A draft that sounds like you.
Colors trace which past passages shaped each word.
It gets smarter as you use it
Traditional TM grows by accumulating entries. The more entries you have, the more noise you have. Over time, TMs require dedicated cleanup sprints just to stay useful.
Living Memory works differently. Every translation decision is absorbed as signal. It learns your team's preferences, tracks how your approach evolves, and becomes more precise about what kinds of suggestions actually fit your project.
The result is a knowledge base that compounds — not a database that degrades.
Living Memory begins learning your terminology preferences, audience level, and voice from the first few translated passages.
Suggestions get noticeably more relevant. Tone, register, and theological or domain-specific nuances are accounted for. Corrections become rarer.
A rich, contextual knowledge base of your team's intent — ready to inform the next project without TM database cleanup.
The Codex Process
Living Memory is what makes Codex's real-time feedback contextually relevant to your specific project, audience, and voice. Together they form a complete continuous translation workflow.
Stop repeating old decisions.
Start building project wisdom.
Download Codex and replace your Translation Memory with something that actually learns.