What is Computer-Assisted Translation (CAT) software?

Global business is powered by language. In 2020, 75% of internet users were not native English speakers, which means organizations that rely on a single language miss most of the world. Modern content teams juggle product documentation, marketing copy, support articles and legal agreements across dozens of languages. Without the right tools, that work is chaotic: translators copy and paste text from PDFs, re‑translate the same phrase hundreds of times and hope that product names remain consistent. It is no wonder that 88 percent of professional translators use at least one computer‑assisted translation (CAT) tool. Translation memories can boost productivity by 40–60% because they reuse previous translations rather than forcing linguists to start from scratch. The same source text is often repeated across manuals, marketing materials and online content, and reusing it not only saves time but also ensures brand consistency.

This article demystifies CAT tools and explains why they are indispensable for localization strategies. We will explore their core components, compare them with machine translation, examine how they improve speed and quality, and show how AI‑powered workflows are evolving. CAT tools are not just for linguists; product managers, marketers and customer‑support teams also benefit because these platforms improve collaboration and shorten time to market. By the end, you will understand why they are quietly running global communication.

What is Computer‑Assisted Translation (CAT) software?

Computer‑assisted translation (CAT) software is software that helps human translators work faster and more consistently by organizing and reusing translated content. It provides a bilingual editing environment where the source text and translation appear side by side. The software segments the source into manageable units (sentences or phrases) and stores each completed translation in a translation memory. When a similar phrase appears later, the CAT tool suggests the previous translation, allowing the translator to accept or modify it. In plain terms, a CAT tool behaves like a smart dictionary and memory combined: it remembers how you translated phrases before and offers those translations, so you don’t repeat yourself. Crucially, CAT tools assist humans; they do not translate automatically.

To summarize: A CAT tool is a platform that manages and accelerates human translation by combining translation memory, terminology tools and quality checks in a single workspace. Using a CAT tool means you spend less time retyping previous translations; your terminology stays consistent, and your final documents maintain the original formatting.

How CAT tools support (but not replace) human translators

CAT tools are often confused with machine translation (MT), but they serve a different purpose. CAT tools provide an interface for submitting, editing and storing multilingual content, whereas machine translation automatically translates text using algorithms In a CAT tool, the human translator leads the way. They view the suggested translation, accept or modify it and then move on to the next segment. The tool may integrate MT engines such as Deep L or Google to pre‑translate a segment, but the human always reviews and edits the draft.

Another important distinction is that CAT tools break the text into segments and preserve formatting and code tags. They remove HTML, XML or design‑tool tags from the editing view, so the translator only sees the text that needs to be translated. When the translation is exported, the original formatting is restored automatically. This segmentation and tag handling mean that translators can focus on language rather than technical details.

Why businesses, teams and freelancers rely on them daily

Businesses adopt CAT software because it helps scale translation without sacrificing quality. The purpose of using CAT tools is to improve translation efficiency and consistency. Translation memories recall approved translations, terminology databases enforce correct terminology, and quality‑assurance checks flag errors before delivery. Cloud‑based CAT platforms allow distributed teams to collaborate in real time. Freelance translators appreciate that they can build personal translation memories and glossaries to enhance productivity across clients. Large enterprises use centralised CAT tools to guarantee that product names, legal phrases and marketing slogans are translated identically across departments and markets.

Core components of a CAT tool

Modern CAT platforms share several foundational components that work together to make translation efficient. Understanding these parts reveals why CAT tools are more than just glorified text editors.

Translation Memory (TM)

A translation memory is a database that stores previously translated segments (sentences or phrases). When a translator encounters a similar segment later, the tool suggests the stored translation. This is particularly useful for repetitive content such as product descriptions, legal documents or user manuals. For example, suppose a company’s e‑commerce platform lists hundreds of products with similar descriptions. After translating “Add to cart” once, the translation memory will automatically suggest that translation whenever the phrase appears again. Because translation memories can match identical segments (100%) or similar segments (fuzzy matches), a translator can accept, edit or discard the suggestions. Real‑world results show that translation memories speed translation by 40–60% and can boost daily output by 30–50 percent.

Terminology / Glossary

CAT tools often include a terminology management module (sometimes called a term base). This database stores approved translations for specific terms, including definitions, context notes and approval status. Terminology is especially important in technical, medical or branded content where using the wrong term can cause confusion or legal problems. For example, a company may prefer to translate “server” as serveur and never as serveuse in French. Glossaries protect the brand voice, ensure compliance and reduce reviewer corrections. TextUnited’s platform, for instance, automatically extracts glossaries and applies them in the background so that translators always use the correct terms.

Bilingual editor

The bilingual editor is the translator’s workspace. It displays the source segment and target segment side by side. Segmentation helps translators focus on one unit at a time and maintain structure. A typical editor also shows translation memory matches, terminology suggestions and comments from reviewers. Modern editors support in‑context preview, allowing translators to view the translation in its final layout (e.g., a website or software interface). TextUnited’s built‑in CAT tool offers a user‑friendly workbench with integrated translation memories and terminology tools, so linguists do not need separate software.

Quality Assurance checks

Quality‑assurance (QA) features act like a grammar checker for translation. They flag inconsistencies, missing numbers, punctuation errors, mis‑placed tags or deviations from approved terminology. QA checks can run automatically while the translator works or as a final step before delivery. For example, if a translation omits a placeholder like %username%, the QA system will warn the translator. These automated checks are critical because they catch small errors that could break code or confuse users.

Machine Translation integrations (including AI‑enhanced MT)

Modern CAT tools integrate machine translation (MT) engines to pre‑translate content. Translators can pre‑translate a document using engines like DeepL, Google or Microsoft and then post‑edit the output. Machine translation is particularly useful for high‑volume, low‑visibility content like support articles. Many CAT platforms also use AI to offer predictive suggestions and fuzzy matches. These suggestions speed up translation but still allow the human to control the final wording. Tools such as TextUnited even incorporate neural machine translation models and large language models that can be customised to specific domains.

The 5 everyday problems CAT tools instantly solve

1. Repetitive translation work: Translating similar phrases repeatedly wastes time and increases the risk of inconsistency. Translation memories reuse previous translations to avoid duplication.
2. Terminology chaos: Without a termbase, teams translate product names or technical terms differently across documents. Terminology management enforces approved terms and brand voice.
3. Formatting headaches: Copying text from PDFs or design files often strips formatting. CAT tools maintain formatting and code tags, exporting translations that mirror the original layout.
4. Lack of collaboration: Emailing files back and forth is inefficient. Cloud‑based CAT tools let multiple translators and reviewers work on the same project simultaneously.
5. Quality errors: Spelling mistakes, missing numbers or inconsistent term usage slip through manual checks. Automated QA catches these issues early.

CAT tools vs Machine Translation: They are not the same

Machine translation (MT) and CAT tools are often mentioned together, but they serve fundamentally different roles. Understanding the distinction helps you choose the right technology for your needs.

How people confuse MT with CAT

MT tools like Google Translate automatically translate source text into another language using statistical or neural algorithms. In contrast, CAT tools support human translators; they segment the source, store translations and provide suggestions. People sometimes conflate the two because modern CAT tools integrate machine translation engines to pre‑translate segments. However, the human translator still reviews and edits the output. Without a human in the loop, pure machine translation may produce literal or awkward translations that fail to capture tone or cultural nuance.

Why MT alone cannot ensure consistency or quality

Machine translation excels at speed and bulk output, making it ideal for large datasets like product catalogues. Yet AI models struggle with idiomatic expressions, cultural references and specialized terminology. They lack the context awareness necessary for marketing copy, legal texts or regulated industries. Without human post‑editing, machine translations risk damaging brand voice or producing errors that could have legal ramifications. Additionally, pure MT cannot maintain a consistent translation across multiple documents because it does not use a persistent translation memory or terminological glossaries.

How CAT tools wrap MT into a structured workflow

CAT platforms combine the best of MT and human translation. They allow translators to pre‑translate segments with machine engines and then refine them using translation memory and termbases. A typical hybrid workflow involves segmenting content, applying machine translation, post‑editing the output, and saving the final translation in the memory. This loop ensures that human expertise corrects machine errors, and AI benefits from the growing translation memory. TextUnited’s fine‑tuning loop exemplifies this process: machine‑translated content is looped back through translator review, which enriches the translation memory and improves future AI output.

CAT tools vs Machine translation: What each does (comparison table)

How CAT tools improve translation speed, accuracy & consistency

How translation memory reuse reduces time and cost

Translation memory (TM) eliminates redundant work. Each time you translate a segment, the TM stores it and suggests it the next time a similar segment appears. This reduces the amount of content you need to translate manually and speeds up time to market. Studies show that TMs can speed translation time by up to 40–60% and allow linguists to translate 30–50 percent more content per day. Because many corporate documents share common phrases (e.g., legal clauses, product descriptions, support articles), the savings compound over time. Saving time also translates to cost savings: you pay less for translation when fewer words need to be translated from scratch.

How glossaries protect brand voice and product terminology

Consistent terminology is vital for brand recognition and compliance. A termbase stores approved translations for brand names, product features and industry‑specific terms. It prevents translators from inventing variations that could confuse customers or violate regulatory requirements. For example, if your company sells “SmartHome Hub,” the termbase ensures it is never translated literally as “maison intelligente.” Glossaries also improve translation quality because translators spend less time searching for the right term

How the bilingual editor removes ambiguity

By splitting text into segments and showing source and target fields side by side, the bilingual editor helps translators focus on one idea at a time. It reduces cognitive overload and makes it easier to apply translation memory matches. In‑context previews allow you to see how the translation will appear on a website or in software, reducing rework after layout changes.

How QA checks prevent tiny but costly errors

Automated quality‑assurance checks catch many errors before a document reaches a client. QA features can identifyinconsistent translations, missing tags, number mismatches or terminology violations. These checks reduce the risk of shipping flawed translations that could confuse users or break software. In regulated industries like finance or healthcare, such errors can lead to fines or legal liability, so automated QA is crucial.

Introduction to MT + human refinements

Machine translation offers speed but requires human oversight. Integrating MT into a CAT tool allows translators to pre‑translate content and then post‑edit it. The hybrid approach combines machine speed with human quality. Because the CAT tool stores the final, edited translation in the memory, the quality of machine suggestions improves over time. This synergy is particularly useful for repetitive or low‑visibility content where perfect nuance is less critical.

How CAT tools fit into modern AI translation workflows

Why CAT tools are even more important in the era of AI

AI translation has made remarkable strides,neural machine translation (NMT) uses deep learning to generate more natural‑sounding translations. AI excels at handling large, repetitive datasets quickly. However, AI alone cannot understand idiomatic expressions or cultural subtleties. As translation volumes grow, human translators need assistance to manage AI‑generated output, maintainquality and protect brand voice. CAT tools provide this structure by organizing AI suggestions and storing corrected translations in a memory. Therefore, far from replacing CAT tools, AI makes them more necessary.

AI‑powered MT inside CAT tools

Modern CAT platforms include machine translation engines and large language models as part of the workflow. TextUnited supplies neural machine translation, generative AI and multiple engine options (Google, Microsoft, Amazon, etc.) within its platform. Translators can pre‑translate segments using these engines, then refine them with translation memories and glossaries. Some platforms offer predictive suggestions and fuzzy matches powered by AI. Others implement dynamic machine learning that learns from post‑editing: for example, if you change a translation in one place, the tool applies that correction across all identical segments. The result is continuous quality improvement and reduced manual editing.

The evolution toward hybrid human‑AI workflows

Hybrid workflows combine AI speed with human judgement. The hybrid translation process typically follows these steps:

1. Content segmentation: Determine which parts of the content are suitable for machine translation (e.g., FAQs or product listings) and which require human creativity (e.g., marketing slogans or legal text).
2. Machine translation: Use AI engines to produce an initial draft quickly.
3. Human post‑editing: Professional linguists review and polish the machine output, correcting errors, refining tone and ensuring terminology consistency.
4. Terminology management: Apply approved glossaries and style guides to maintain brand voice.
5. Quality assurance: Run automated QA checks to verify compliance with client requirements and catch any remaining issues.
6. In‑market review: (Optional) Have native speakers review the translation to ensure cultural resonance.

By integrating these steps into a single platform, CAT tools ensure that AI and humans reinforce each other. TextUnited’s fine‑tuning loop automatically loops machine‑translated content back through human review to enrich the translation memory, creating a virtuous cycle of improvement.

How TextUnited implements AI responsibly

TextUnited’s platform is built around a human‑in‑the‑loop AI workflow. The system centralizes translation memories, glossaries and style guides and uses this language data to power AI translation and quality estimates. A built‑in CAT tool allows linguists to access translation memory and terminology without needing third‑party software.Live translation memory reuses translations in real time, while terminology management keeps brand vocabulary consistent. The fine‑tuning loop ensures that corrections feed back into the AI and translation memory, and the centralized language assets feature automatically extracts glossaries and builds translation memories. Quality assurance features include query management and in‑context review to catch translation issues early. This integrated approach offers speed and consistency without sacrificing human oversight.

Where CAT tools are used: Everyday use cases anyone can relate to

CAT tools have moved beyond specializedlocalization departments; they are used across many teams and scenarios:

• Product documentation updates: Technical writers maintain manuals, help articles and release notes for software and hardware. CAT tools reuse existing translations, ensuring consistent terminology and quick turnaround for new versions.
• Marketing content: Marketing teams translate blog posts, landing pages and ads into multiple languages while preserving tone and brand voice. Glossaries ensure slogans and product names are used consistently.
• Customer support: Support teams translate knowledge‑base articles, FAQs and chat responses to serve global audiences more efficiently. Translation memories reuse common responses and reduce response time.
• Legal and compliance: Legal departments translate contracts, privacy policies and regulatory documents, where precision is essential. Terminology management and QA checks help avoid costly mistakes.
• eCommerce listings: Retailers translate thousands of product descriptions, specifications and reviews across marketplaces. Translation memories save time on repetitive descriptions, and MT integration speeds low‑visibility content.
• Technical training content: Training teams localize instructional videos, course materials and certification exams. CAT tools ensure the same technical term appears consistently across modules and languages.

CAT tools inside TextUnited

TextUnited is a Language AI & Translation System that integrates a built‑in CAT tool with AI translation and human‑in‑the‑loop workflows. The platform serves as a central hub for translation memories, glossaries and style guides. It supplies AI with relevant language data and provides translators with a user‑friendly workbench that eliminates the need for third‑party software.

Here’s how TextUnited enhances CAT-based translation with its real product features:

• Centralized Translation Memory (TM)

Your company’s translations grow into a shared, living asset.
TextUnited automatically stores every approved segment and reuses it across teams, reducing repetition and cutting translation time by up to 80%. It also becomes the data foundation for AI quality improvement and MT customization.

• Terminology Control & Enforcement

Instead of hoping translators use the right terms, TextUnited actively enforces them.
The system highlights approved terminology, flags violations, and prevents incorrect word choices across all projects, keeping brand voice consistent everywhere.

• Supervised AI Translation

AI handles the initial speed; human expertise guarantees the quality.
TextUnited blends neural MT, supervised AI, and human post-editing in a loop that continuously improves your results. Every correction enriches TM, enhances glossaries, and trains the system for next time.

• Automated Workflows

No more emailing files, chasing reviewers, or manually routing documents.
TextUnited moves each project through predefined steps: preprocessing, translation, human review, LLM review (optional), approval, and delivery. Teams save hours of coordination effort.

• Unified Translation Management Platform

All languages, files, translators, reviewers, style guides, and assets live in one interface.
No separate CAT tool, MT engine, glossary app, or project tracker. Everything is integrated.

• Reuse of Previous Translations

The platform identifies identical or similar content instantly and applies existing translations automatically, removing repetitive work and ensuring perfect consistency.

• AI–Human Workflow Modes

Different content needs different levels of quality. TextUnited lets teams pick from:

• AI draft
• Human-refined MT
• Full human translation
• Expert review
• LLM review for fluency

This flexibility gives organizations control over cost, quality, and turnaround time.

• Approval Workflow

To ensure accountability, all translations pass through structured approval layers.
No more guessing who signed off or why changes were made.

• Continuous Improvement Engine

Every translator correction, terminology update, and client edit feeds back into the system.
Your language assets improve automatically with every project.

• LLM Review (Optional)

For certain content types, TextUnited can apply an LLM-based fluency layer, producing natural, native-like text while keeping terminology and meaning intact.

• Style Enforcement

Brand tone and writing rules are applied throughout the translation process.
The system flags tone mismatches and ensures the translated text reads like your brand, not like a machine.

• Translate Files Fast

Non-technical team members can drop a file into TextUnited and get a full translation workflow instantly - powered by AI, translation memory, terminology, and human refinement.

Imagine a product team pushing a new UI update in ten languages.
They upload the strings into TextUnited → TM auto-fills repeated phrases → terminology ensures button labels stay consistent → AI drafts the rest → linguists post-edit → QA catches formatting issues → final text goes to approval → everything updates in the background for next time.

Fast, controlled, consistent - without chaos.

Getting started: What to look for in a CAT tool

Choosing your first CAT tool can feel overwhelming because there are many products on the market. Here are practical considerations to help you select a tool that suits your needs:

1. Essential features: Look for core components - translation memory, terminology management, segmentation and quality‑assurance checks. According to the Phrase guide, modern CAT tools share these features. Without them, you will not benefit from the speed and consistency gains.
2. User experience: An intuitive interface saves time. The Phrase article recommends choosing a flexible and user‑friendly CAT editor with a simple dashboard, clear navigation and good support. If your team is non‑technical, avoid tools with steep learning curves.
3. Collaboration and cloud vs desktop: Decide whether you need a cloud‑based or desktop‑based tool. Cloud tools enable real‑time collaboration across teams and devices but require internet access. Desktop tools offer more control and may be preferred for offline or highly secure projects.
4. Integration: Ensure the tool integrates with your content management systems, design software or localization platforms. Modern CAT tools often connect with CMS, Git repositories, and marketing platforms.
5. Machine translation and AI: Look for built‑in MT and AI features that provide pre‑translation and predictive suggestions. However, ensure you can customize and control these engines so they align with your domain.
6. Security and compliance: If you handle sensitive data (e.g., legal or medical documents), choose a tool with robust security and data‑protection measures. Remember that web‑based tools may pose confidentiality risks.
7. Pricing and scalability: Decide on your budget and consider whether the tool offers a free trial. Some tools scale better than others: make sure the tool can handle multiple languages, projects and workflows as your needs grow.

Testing the tool on a small project before committing helps ensure it meets your requirements and fits your team’s workflow. Many vendors (including TextUnited) offer free trials so you can evaluate features without risk.

Conclusion: CAT tools are quietly running global communication

Computer‑assisted translation tools have evolved from simple translation aids into central platforms for global content operations. They provide translation memories, terminological databases, segmentation, machine‑translation integration and automated quality checks, all in a single workbench. The combination of human expertise and AI‑powered suggestions makes translation faster, more consistent and more cost‑effective. With modern platforms like TextUnited, translation workflows are organized into structured, hybrid processes that balance speed with nuance. As global markets continue to demand multilingual content, CAT tools will only grow in importance. Adopting a beginner‑friendly tool now equips your team to handle increasing translation volumes with confidence.