Shindan gives you an objective view of your localization quality, so your effort and budget go to the content that actually needs attention.
Shindan, Alpha CRC’s AI-powered language quality evaluation tool, optimizes your workflows, enabling you to get more translation from your budget. Shindan uses an agentic AI network, alongside a parametric approach to quality evaluation, to identify which content needs human review and which is error-free and ready for release. Your linguists apply human judgment only where the output genuinely needs it.
As more businesses adopt machine translation and AI-enabled technologies, the question of localization quality assurance is becoming increasingly important. Our platform enables businesses to analyze their AI translation quality over time, gaining deeper insights into their localization processes. For companies producing multilingual content at scale, that ongoing visibility represents a crucial learning curve.
Shindan offers users a holistic view of your localization output quality, with a suite of use cases to help you optimize your budgets and, crucially, your return on investment.
Our parametric quality evaluation automatically identifies which content requires human review and which already meets your quality standards for linguistic accuracy. This scalable approach reduces review time and optimizes your budget, ensuring you can localize more of your content for greater reach across global markets.
Shindan analyzes text and screenshots to identify in-context issues like text truncation. It integrates seamlessly into existing linguistic quality assurance (LQA) workflows by reporting directly to tools like JIRA via API, or flagging items for human review.
Shindan measures translation output over time, using objective, automated metrics. It goes beyond traditional quality metrics, spotting patterns and shifts in your production pipeline for a clearer view of your translation process.
We believe that every business has unique quality expectations. That’s why we’ve built Shindan to be fully customizable and responsive, ensuring all your assessments are relevant to you.
If you are still defining what quality means for your program, Shindan’s standard model uses the ISO 5060 quality framework as a base, by means of a tweaked set of categories and weights to ensure optimal AI assessment. During onboarding, we will work together to understand your primary measure of quality and configure Shindan around it.
Shindan can be used across your workflows to perform a range of tasks. It filters strings out of the human post-editing process and provides an objective view of quality in any target languages that your team cannot continuously evaluate.
Thanks to Shindan’s intelligent assessment, you can focus your localization spend on the content that needs it most. Using your assessment criteria, Shindan filters high-quality content out of the human editing workflow and sends it straight to delivery, allowing you to localize more content without increasing your budget.
Our teams will work alongside you to identify the best ways to integrate Shindan into your AI-assisted workflows. We will help you analyze:
We understand that each use case is different, which is why we’ve designed Shindan to be as flexible as possible. One common pain point is that companies don’t know how much of their material has been quality assessed, or when intervention was needed, but not actioned.
See how Shindan can reduce your review costs and localize more content. Talk to Alpha CRC today.
Translation quality assurance is the process of evaluating translated content against a defined set of criteria before it reaches your target audience. Traditionally, this has relied on human evaluation, with linguists reviewing output segment by segment.
Shindan automates the triage stage of this process, routing each segment based on whether it meets your threshold. It works on human output and AI-generated translations alike.
Your human experts work only on content that needs their input, so your translation quality assurance process runs faster without reducing the standard of the final output. Content that needs attention is sent for post-editing. Shindan integrates directly with tools like JIRA via API to fit within your existing systems rather than requiring a separate process.
Shindan sits between translation and delivery. Once files come back from augmented translation, whether that is human translation, NMT, or LLM output, Shindan assesses each segment and routes it accordingly. The output can come from a human translator, machine translation engines, or large language models.
For teams working on machine translation engine training, Shindan’s output data also feeds directly into the tool to identify where engines need improvement.
Shindan is content-agnostic and language-agnostic by design. Alpha CRC’s testing shows over 90% accuracy in identifying output that needs human review, with some language pairs reaching over 99%. This level of precision comes from how Shindan is built, rather than a single artificial intelligence system evaluating everything at once.
The agentic network splits the work between specialist agents, each focused on a specific part of the quality assessment, such as:
Accurate terminology
Style guide compliance
Formatting
Since each agent has a narrower task, the output is more consistent and more reliable than single-model methodologies. If you want to know what to expect before you get started, our team can run a scoping exercise and provide benchmarks for your languages.
Yes. For clients using Alpha CRC’s bespoke language models, Shindan evaluates their output against your brand-specific quality criteria, keeping production and performance in close alignment.
For clients working on LLM fine-tuning, Shindan provides structured, objective data on how models perform across multiple languages and file types to show you where additional training data is needed.
Shindan’s standard model is built on the ISO 5060, a translation quality evaluation framework, with categories and weights adjusted to suit AI-based assessment. This can be further configured during onboarding using your own glossaries, style guides, and approved translation memory, so assessments reflect your specific quality definition rather than a generic standard. Most clients find that combining the standard model with their own assets gives the most accurate picture of overall quality across their languages.
Shindan was built by Alpha CRC and is not licensed or resold. Every aspect of the product draws on the same expertise that has run our localization work since 1987. The configuration conversations are informed by real program experience. We work with you to define quality thresholds and identify where Shindan adds the greatest potential across your files and languages.
Alpha CRC is ISO 27001 certified. Your linguistic assets, translation memory, and bilingual output stay within a controlled environment throughout. For enterprises in regulated industries where data sovereignty is a baseline requirement, these factors apply to Shindan just as it does to our translation and localization services. Smart. Human. Global.
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Since 1987, Alpha CRC has provided clients around the world with expert localization services. From humble beginnings in translation to full content creation and multilingual voiceover production, we’ve spent the last four decades honing our craft, working tirelessly to polish translation quality and help customers engage with their global audiences. Now, almost forty years after […]
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At Alpha CRC, our four decades of localization expertise informed every decision in developing Shindan, our proprietary language quality management platform. But the path to creating a production-ready AI system that could meet the exacting standards of professional localization wasn’t straightforward. The technical evolution of Shindan, from a promising but unreliable single-AI system to today’s […]
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