Alconost is a tech-driven localization company building an ecosystem of products around localization and QA.
Since 2004, we've helped companies of all sizes, from indie app and game developers to industry leaders, reach audiences in 120+ languages. We combine linguistic expertise, cultural intelligence, and advanced technology to handle every aspect of global expansion.
Flexible teams, purpose-fit service levels for any budget, and effective delivery at any volume and speed.
This is the 7th launch from Alconost Localization. View more
QACAT
Launching today
QACAT is a hybrid translation QA platform combining automated rule checks, AI analysis, and expert human review. Upload screenshots and review translations in real product UI — built-in OCR pulls the text for you. Every run gives a structured, scored report with severity breakdowns and an AI summary of what to fix. Works across 100+ languages. Powered by Alconost.
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Launch Team
How does it perform at scale? Wondering if it's been tested on projects with, say, 40+ languages.
Alconost Localization
@elena_kozak Thank you for your question - and yes! QACAT has already been used across 40+ languages in production environments. Not necessarily within a single project, but across multiple real-world localization workflows and quality evaluation scenarios.
How does the OCR handle languages with non-Latin scripts or right-to-left text like Arabic or Hebrew?
Alconost Localization
@margarita_tsygankova Thanks for asking. Good question indeed! We use two OCR engines. One supports Arabic, Hebrew (AI assisted), and other non-Latin scripts well (no AI involved, for NDA safe mode), while the other is optimized for Latin-based languages. We select the most suitable OCR approach based on the content being processed.
Hi! I am wondering how this is different from just running a quick LLM QA check myself?
Alconost Localization
@olga_sapach Quick LLM QA checks are absolutely a valid modern approach, and I use them myself. The difference is that QACAT combines multiple quality layers rather than relying on a single AI opinion.
Depending on the workflow, that can include deterministic QA checks, + LLM-based evaluation, +human validation, and + deeper review workflows such as LQA or LQT.
In our experience, even the best and most expensive LLM models are excellent at finding some types of issues, but they still miss context, make incorrect assumptions, or generate false positives. That’s why we treat AI as one layer of the quality process rather than the final authority.
Alconost Localization
Well done Dmitry - the feature choices show this platform was built by someone with a lot of hands-on localization experience =) agree that handling glossary terms is a must! when I was working on Nitro, glossary feature was often asked about, so we added it too.
Alconost Localization
@dioiv Thanks a lot. I love and miss Nitro.
Congrats on the launch! You've put a lot of work into this platform. I personally like that you can pick how deep the QA goes - makes sense that not everything needs the full treatment
Alconost Localization
@nickzaleski Thank for your inspiration, master :)
finally a QA tool that treats quality as something you track over time rather than a one-off score per project!