... built-in  AI Reviewers  ship: a  glossary reviewer  and an  instructions reviewer . Toggle on the glossary

... triage workflow  reads any Jira ticket about a bad translation, looks at the offending output, and proposes the actual fix in the  engine config : a  glossary item  to add, an  instruction  to tighten, a  model config  to adjust. Review the suggestion, accept or edit it, and the engine is fixed for every future translation not just the one that was reported. Also shipped AI Reviewers   now receive the same context ... ... localizer saw.  Brand voice, instructions, and glossary

... stateful translation APIs that you configure once and call from backend code,  MCP , or  CI/CD . Before today, every team that wanted consistent terminology, on-brand tone, and per-locale rules wired it up by hand: a glossary in one repo, brand-voice notes in a Notion doc, prompt scaffolding hard-coded into the app. The engine collapses all of that into a single addressable thing. What's in the launch Localization engines .  Configure models, brand voice, instructions ... ... glossaries

... Audit logs are now available an append-only record of every state-changing action in your organization. Each change to engines, glossaries, instructions, brand voices, AI reviewers, API keys, members, and roles is captured with the actor, action, target, and request context. The log lives in the dashboard and filters by user, action category, target, and date so you can see exactly who created, updated, or removed a glossary

... Localization Engine Suggestions are concrete edits to a localization engine a glossary entry, an instruction, or a brand-voice change proposed by the platform from its own AI Reviewer verdicts. When reviews on a translation come back low, the platform suggests a specific edit to the localization engine's glossary

... structural metadata rather than translatable content stay verbatim across target locales and bypass the LLM entirely. Logs show the context that produced each translation.  Open any request in the Log tab and you can see exactly which  glossary terms ,  instructions , and  brand-voice rules  the engine retrieved plus the glossary

... async localization API  fans out a single localization request across every target locale in one POST and delivers results via webhook. Source payload in, job IDs out, webhook fires per locale as each finishes. Also shipped Glossary   CSV upload.  Bulk-import glossary

... many found they were invisible. But here's what scared me more: Of those who WERE visible, 43% had incorrect information in AI answers. Not "suboptimal." Not "could be better." Wrong. Outdated pricing. Missing features. Wrong founder bios. Competitors credited for your work. And the average error sticks around for 4 6 months . Today, I'm sharing the full dataset: 1,000+ SaaS products, 75,000+ AI answers, and the hard truth about what's being said about you when ... ... analyzed 50 brands that discovered errors and tracked the impact. Error Type Average Revenue Impact Pricing error (higher than actual) 47,000 Pricing error (lower than actual) 23,000 (leakage) Missing critical feature 38,000 Wrong positioning (enterprise vs

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