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Build, run, and debug your multilingual AI prompt pipelines for any text-based task
Leverage your linguistic context such as TMs, glossaries, and style guides
Use any LLM combination by Bringing Your Own API Keys. No AI vendor lock-in!
THE CHALLENGE
Getting AI to work reliably in localization requires solving four hard problems at once.
01
GPT-5.1 for translation? Opus 4.6 for quality eval? An open-source reasoning model for accuracy? Every combination could give you an edge over competition, saving costs and/or reducing risk.
02
TMs, glossaries, style guides, post-edits, LQA scorecards — they live in your systems, not inside the LLM’s brain. Before an LLM can use any of them, you have to "teach" it to do so.
03
Without structured benchmarking you’re basically guessing. Your stakeholders need proof, not vibes — especially if your profit margins depends on this.
04
One-off prompts with a single file uploaded in ChatGPT don’t scale. You need a way to run consistent AI-powered pipelines across all of your language pairs, content types, and brands.
The complete Build → Test → Run → Monitor loop lives in ContentQuo AI Studio which ContentQuo Prompt is part of.
Prompt Engineering
Most teams using AI for localization get generic results because they use generic prompts. What an AI model does with your content depends entirely on what you put in front of it — the instructions, the context, the constraints. Inject the right glossary, and it uses your approved terminology. Add a TM and a style guide, and it mirrors your established style. Without that context, the model decides for you.
ContentQuo Prompt gives you a visual IDE to build any text-centric content transformation as a reusable template — no code required. Create your own custom AI translators, AI quality evaluators, AI summarizers, AI content writers. Every action is versioned, testable, and deployable via API.
ContentQuo AI Studio works with any commercial AI model like OpenAI ChatGPT, Anthropic Claude, and Google Gemini. It also works with any open-source models like LLaMA. Leverage your corporate approved AI provider by bringin your own API Key. Mix & match any LLMs per language or content type or prompt.
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HOW TO USE IT
ContentQuo Prompt isn't an orchestrator or a workflow designer — it's a factory for building AI "blocks" that you can then orchestrate. Small teams can run them directly from the UI by uploading & downloading files. Larger organizations can plug them into their automation & orchestration pipelines via ContentQuo Runner API.
UI — for SMALLER TEAMS OR EXPERIMENTS
Our visual editor lets you design, build, test, and run multilingual AI workflows yourself. Import your TMs, pick your AI models, write your prompts — and then your team can run what you built on 100 XLIFFs right from the browser. Ideal for day-to-usage in small and mid-size teams, as well as for experimenting in larger teams.
Runner API — for EXECUTION AT scale
Deploy your validated AI actions in 1 click to call them from Blackbird, Phrase Orchestrator, Crowdin, n8n, or your own code. Send gigabyte-scale TMs as context via Amazon S3 compatible storage. The orchestration layer is yours to bring — we just handle execution. Ideal for enterprises and larger LSPs.
AI POWERED TRANSLATION QUALITY EVALUATION (AI LQA)
Translation quality evaluation is where most AI localization tools fall short. ContentQuo Prompt natively supports Quality Evaluators — structured pipelines that automate MQM-style LQA and Adequacy-Fluency style quality evaluation using your own linguistic standards and your TMs/style guides/glossaries, not generic AI guesses.
WHY IT MATTERS
ChatGPT will tell you a translation is good. It won't give you structured MQM errors, severity levels, or deduplicated issue sets your reviewers can act on.
WHAT YOU GET
The Checker → Categorizer → Distiller pipeline finds issues, classifies by MQM category and severity, then deduplicates — so reviewers get clean, actionable errors.
YOUR STANDARDS
Inject your LQA scorecards, previous translation errors, and linguistic rules as RAG context. Each AI quality evaluator will apply your custom standards — not just generic quality definitions.
A purpose-built language quality evaluation pipeline — consistent, categorized, and ready for human review every time.
Checker
Finds error candidates
Categorizer
MQM + severity
Distiller
Removes duplicates
OUTPUT
12 candidate issues → 4 confirmed issues · Categorized · Severity assigned · Ready for human validation or scoring
BUILT FOR LOCALIZATION TEAMS MOVING INTO AI ENGINEERING
You're already managing TMs, glossaries, and vendor quality. Get the infrastructure to easily handle AI prompt engineering & context engineering too — without building every single thing yourselves.
Create and ship multilingual AI workflows yourself. No tickets, no waiting, no external dependencies. Just talk to our AI assistant, and it will build things for you.
Benchmark against your historical human data across languages, models, prompts, and context to understand exactly how well AI performs today and how to improve it.
TAKE CONTROL
It's no longer enough to "just manage localization" in order to keep your budgets & your headcounts. Prove that you can actually handle multilingual AI engineering, and build on top of it in order to secure your Localization team's success in the AI age.
Your team can decide which model runs, what context it uses, and what quality bar it must clear — before a single segment goes live.
Benchmark AI performance against your human gold standard. Replace vendor claims with numbers your stakeholders will actually trust.
Your linguistic expertise plus verifiable quality data makes you the expert that engineering and leadership actually listen to.
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