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Copy file name to clipboardExpand all lines: frontend/src/i18n/locales/en.ts
+50-7Lines changed: 50 additions & 7 deletions
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@@ -404,19 +404,20 @@ export const en = {
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"onboarding.limitedModeWorks": "Crawl-based SEO checks, Google Search snapshots, and community discovery still run from the URL-first flow.",
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"onboarding.limitedModeNeedsKeyTitle": "Works better with a key",
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"onboarding.limitedModeNeedsKey": "AI-assisted keyword extraction, automatic competitor context, and broader AI Search checks need a configured provider.",
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"landing.headerTagline": "Search, AI visibility, and next actions.",
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"landing.metaTitle": "OpenCMO | Open-source AI CMO for developer products",
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"landing.metaDescription": "OpenCMO helps developer products understand how they show up in search, AI answers, and developer communities, then turns those signals into next actions.",
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"landing.headerTagline": "Visibility work that learns each loop.",
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"landing.metaTitle": "OpenCMO | Open-source AI CMO that learns from every scan",
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"landing.metaDescription": "OpenCMO is an open-source AI CMO for developer products, turning search, AI visibility, community signals, approvals, and follow-up scans into one compounding visibility system.",
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"landing.navOpenSource": "Open source",
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"landing.navPlatform": "First scan",
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"landing.navLearning": "Learning loop",
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"landing.navWorkflow": "Workflow",
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"landing.navBlog": "Blog",
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"landing.navTrust": "Trust",
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"landing.navMentions": "Mentions",
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"landing.navFaq": "FAQ",
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"landing.heroEyebrow": "Open-source AI CMO for developer products",
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"landing.heroTitle": "Run one scan to see how your product is understood across search, AI answers, and community.",
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"landing.heroSubtitle": "OpenCMO turns the first scan into one working brief: site-health blockers, AI-search gaps, community demand, and the next move to ship.",
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"landing.heroEyebrow": "Open-source AI CMO system",
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"landing.heroTitle": "A visibility operating system that learns from every scan.",
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"landing.heroSubtitle": "OpenCMO connects search, AI answers, community signals, approvals, and follow-up scans into one evidence trail, so each loop makes the next action sharper.",
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"landing.badge": "Built for open-source projects, developer tools, and technical products that need clear first-run answers.",
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"landing.title": "One open-source AI CMO workspace for search, AI answers, and developer communities.",
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"landing.subtitle": "OpenCMO helps you understand how your brand is discovered by Google, AI assistants, and real communities, then turns those signals into concrete growth actions.",
@@ -456,7 +457,7 @@ export const en = {
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"landing.stage6": "Persist and publish",
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"landing.platformEyebrow": "First scan output",
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"landing.platformTitle": "The first scan should not end as another dashboard.",
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"landing.platformSubtitle": "OpenCMO turns the public evidence into work your team can review, prioritize, and ship.",
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"landing.platformSubtitle": "OpenCMO turns public evidence into work your team can review, prioritize, ship, and measure again.",
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"landing.platform1Title": "Site health and SEO",
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"landing.platform1Desc": "Audit crawlability, Core Web Vitals, metadata, and technical issues before they quietly suppress discovery.",
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"landing.platform2Title": "AI Search visibility",
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"landing.platform4Desc": "Keep competitor context, topic gaps, and market structure close to the scan so strategy stays grounded.",
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"landing.platform5Title": "Reports, approvals, and leads",
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"landing.platform5Desc": "Move from findings into Review & Publish, reports, and developer leads without rebuilding the context in another tool.",
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"landing.learningEyebrow": "Learning loop",
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"landing.learningTitle": "The value compounds when evidence, decisions, and outcomes stay together.",
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"landing.learningSubtitle": "The strongest idea from autonomous marketing systems is not more tools. It is continuity. OpenCMO keeps each scan, review, approved action, and follow-up result attached to the same project context.",
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"landing.learningLoop1Title": "Observe the public surface",
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"landing.learningLoop1Desc": "Capture search, AI-answer, SERP, site-health, and community evidence before the team debates what to do.",
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"landing.learningLoop2Title": "Interpret the drift",
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"landing.learningLoop2Desc": "Compare the new readout with prior context so category mismatch, narrative gaps, and competitor pressure are easier to see.",
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"landing.learningLoop3Title": "Ship with guardrails",
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"landing.learningLoop3Desc": "Route recommendations into reports, approvals, content work, and outbound actions with the evidence still attached.",
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"landing.learningLoop4Title": "Feed the result back",
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"landing.learningLoop4Desc": "Use the next scan to see what changed, what held, and what should be adjusted instead of starting from zero.",
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"landing.learningMemoryEyebrow": "System memory",
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"landing.learningMemoryTitle": "Every run updates the next recommendation.",
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"landing.learningMemoryBody": "OpenCMO is shaped like a workspace because marketing judgment improves when signals, decisions, and shipped work are not scattered across separate tools.",
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"landing.learningMemoryRow1Label": "Baseline",
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"landing.learningMemoryRow1Value": "The first scan captures how the market currently reads the product.",
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"landing.learningMemoryRow2Label": "Decision",
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"landing.learningMemoryRow2Value": "The strongest findings move into review with source evidence and tradeoffs.",
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"landing.learningMemoryRow3Label": "Action",
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"landing.learningMemoryRow3Value": "Approved fixes, reports, replies, and content stay tied to the project.",
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"landing.learningMemoryRow4Label": "Next loop",
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"landing.learningMemoryRow4Value": "Follow-up scans compare the outcome and reset the next priority.",
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"landing.learningStat1Label": "Context",
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"landing.learningStat1Value": "Retained",
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"landing.learningStat2Label": "Decisions",
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"landing.learningStat2Value": "Traceable",
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"landing.learningStat3Label": "Actions",
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"landing.learningStat3Value": "Measurable",
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"landing.workflowEyebrow": "How it works",
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"landing.workflowTitle": "From public signals to the next move.",
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"landing.workflowSubtitle": "Under the hood is a six-stage pipeline. For the team, the promise is simpler: see the gap clearly, then ship the highest-leverage fix.",
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