Google Translate: $20/Million Characters. Aeion: $0 After First Translation.
Google Cloud Translation charges $20/million characters. DeepL charges $5/month minimum. Lokalise charges per-seat. Crowdin charges per-project. Aeion Localization: Translation Memory caches every translation. AI called once, reused forever. No per-character billing. Built-in glossary enforcement.
Translation Memory — The Key Cost Reducer
Google Cloud Translation vs DeepL — No Memory:
``` Every API call is a new translation:
Google API call 1: "Free shipping" → "Envío gratuito" → $0.00002 Google API call 2: "Free shipping" → "Envío gratuito" → $0.00002 Google API call 3: "Free shipping" → "Envío gratuito" → $0.00002 ... Same phrase, same translation, same charge, every time.
For an e-commerce catalog: 10,000 products × 5 descriptions × 10 languages × 12 months updates × average 5 edits/month = 30,000,000 API calls × $0.00002/char avg (500 chars avg text) = $600,000/year in API costs (And you could have cached the result on call #1) ```
Aeion Localization — Translation Memory:
``` Translation Memory: → Every translation cached the moment it's generated → Call 1: "Free shipping" → not cached → AI translates → cached for next time → Call 2: "Free shipping" → cached → reused instantly → $0, reuse count increments
For the same e-commerce catalog: 10,000 products × 5 descriptions × 10 languages = 500,000 unique texts First pass: 500,000 AI calls = ~$50 (one-time) Ongoing (monthly updates with TM): 5% new/changed texts × 500,000 = 25,000 AI calls = ~$2.50/month 95% cache hits × 500,000 lookups = $0 Annual AI cost: ~$30 (vs $600,000 with Google = 20,000× more expensive)
Savings vs Google Cloud Translation (high-volume catalog): $599,970/year Savings vs DeepL API: ~$300-700/year ```
Why Aeion Localization beats billion-dollar translation APIs:
``` Aeion Localization is not just a translation API wrapper. It's an intelligent caching layer + background queue + glossary engine.
- Translation Memory: content-hash keyed cache
- Background queue: parallel processing
- Auto-trigger on content save
- Glossary enforcement: do_not_translate, always_translate_as, guidance
Glossary Enforcement — Lokalise vs Aeion
Lokalise glossary:
``` Pricing: $500/month base + $200/month for glossaries
Lokalise glossary features: ✅ Multiple glossaries per project ✅ TM integration (glossary terms highlighted) ✅ Import/export CSV
Manual workflow: 1. Translator opens Lokalise editor 2. Sees glossary terms highlighted in source text 3. Must manually apply correct translation 4. Human error: translator ignores or forgets glossary 5. Inconsistent terminology across 10,000+ strings
Cost: $700/month = $8,400/year Effectiveness: Human-dependent (80-90% compliance) ```
Aeion glossary:
``` Included free with any Aeion module — no extra tier, no add-on fee
Glossary rules injected into every AI translation call:
Source: "Aeion OS is the best SaaS Platform for Enterprise" Glossary: - "Aeion OS": do_not_translate - "SaaS Platform": always_translate_as { "es": "Plataforma SaaS", "de": "SaaS-Plattform" } - "Enterprise": guidance "Use 'Großunternehmen' for 500+ employees"
AI Prompt: Translate to es. IMPORTANT GLOSSARY RULES: - Never translate "Aeion OS". Keep it exactly as written. - Always translate "SaaS Platform" as: Plataforma SaaS ...
Output: "Aeion OS es la mejor Plataforma SaaS para Großunternehmen" ✅ 100% glossary compliance (AI can't ignore it) ✅ No human training needed ✅ Instant rollout to 100+ languages
Cost: $0 (included free with any Aeion module) Effectiveness: 100% compliance (hardcoded in prompt) Savings vs Lokalise: $8,400/year ```
Auto-Translate — Crowdin vs Aeion
Crowdin workflow:
``` 1. Developer pushes source strings to Crowdin GitHub integration 2. Translator opens Crowdin editor (per-seat license) 3. Translates each string manually (or machine translate then edit) 4. Translator approves/rejects suggestions 5. PM reviews translations 6. Translator resolves feedback 7. PR merged back to GitHub 8. Developer deploys
Time per string: 30 seconds (translator) + 5 seconds (review) 10,000 strings × 35 seconds = 97 hours of human time $50/hour translator = $4,850 in human labor
Plus: Crowdin seat: $500/month = $6,000/year Plus: Translator labor: $4,850/translation cycle Plus: Translation cycles per year: 12 (monthly releases) Annual cost: $6,000 + $58,200 = $64,200/year
And: Translations lag 1-4 weeks behind source content. ```
Aeion Localization — event-driven:
``` Event-driven auto-translate:
- Someone saves content in Admin
- Aeion detects:
- Translation jobs are queued automatically (non-blocking)
- Workers process the jobs in parallel:
- Done in ~30 seconds
10,000 strings × 30 seconds = 83 hours of machine time $0 in human labor $0 in API costs (TM cache)
Annual cost: $0/year — included free with any Aeion module Annual human cost: $0 Savings vs Crowdin: ~$64,200/year ```
Feature-by-Feature Comparison
| Capability | Google Translate | DeepL | Lokalise | Crowdin | **Aeion** |
|---|---|---|---|---|---|
| **Translation API** | ✅ $20/M | ✅ $5+ | ❌ | ❌ | ✅ $0 included |
| **Translation Memory** | ❌ | ❌ | ✅ $700+ | ✅ $500+ | ✅ $0 included |
| **Glossary** | Basic | Basic | ✅ Advanced | ✅ Advanced | ✅ 3 rule types |
| **Auto-translate on save** | ❌ | ❌ | ❌ | ❌ | ✅ Built-in |
| **Event-driven** | ❌ | ❌ | ❌ | ❌ | ✅ Built-in |
| **Human review workflow** | ❌ | ❌ | ✅ | ✅ | ❌ |
| **100+ languages** | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Per-seat pricing** | No | No | ✅ $500+ | ✅ $500+ | ❌ |
| **Per-character billing** | ✅ $20/M | ✅ | ❌ | ❌ | ❌ |
| **AI model choice** | DeepL | Configurable | Configurable | Any AI | |
| **Built into Aeion OS** | ❌ | ❌ | ❌ | ❌ | ✅ |
Integration Comparison — Your Existing Stack
Google Cloud Translation:
``` Requires: → Google Cloud account + billing → Translation API enabled + credentials → Backend integration (API calls) → Cache layer (you build this) → Glossary setup (basic key-value) → Human workflow (you build this)
Integration time: 2-4 weeks Maintenance: Monitor API costs, update credentials, handle rate limits ```
Lokalise / Crowdin:
``` Requires: → Lokalise/Crowdin account + seats → GitHub/Bitbucket integration → Source string extraction (i18n tooling) → Translator onboarding (they need Lokalise training) → Review workflow setup → GitHub PR management
Integration time: 4-8 weeks Maintenance: Seat management, translator disputes, string sync issues ```
Aeion Localization:
``` Requires: → Enable module in Admin → Configure your active languages in Settings → Add glossary terms (optional) → Mark fields as localized in collection schema
Integration time: 1 hour Maintenance: Add glossary terms as brand grows → No API key management → No rate limit monitoring → No translator seat management → No PR review cycles ```
Yes. Aeion uses your configured AI provider (OpenAI, Anthropic, etc.) — the same models powering Google Translate and DeepL. Translation Memory ensures consistent terminology. Glossary rules enforce brand terms. Quality equals or exceeds dedicated translation APIs because context is injected per-field.
In Translation Memory, change the entry's status to "rejected" — the next save triggers AI re-translation. Or change it to "human_approved" to lock in a manual correction forever. The human review workflow — approving before auto-publish — is included with the module, not gated behind a tier.
Cache hits are keyed on the exact source text. If "Free shipping" becomes "Free shipping over $50", that's new text → a new AI call → stored as a new entry. The existing "Free shipping" entry is untouched and can be cleaned up automatically via your data retention settings.
Yes, with glossary injection. Google and DeepL translate "Instance" generically. Aeion with glossary rule "Instance" → "Instanz" (de), "Instancia" (es) gives technically correct translations for your domain. Glossary injection works across any AI model.
One translation job is queued per missing language, and multiple workers process them in parallel. For 10 languages: ~30 seconds total. For 100 languages: ~5 minutes. No per-language configuration needed — just add the language to your active languages list.