This template maintains a single source of truth for your multi-language terminology, brand vocabulary, and UI strings. It connects master terms to target language translations, helping your team eliminate inconsistent phrasing across markets.
Key tables for Terms, Languages, Localizations, and Users work together automatically. Each localization links directly to a source definition, target language code, and reviewer, preventing duplicated definitions or orphaned translations.
Built-in AI fields draft realistic usage examples for source terms and evaluate translation quality against master definitions automatically.
Google Sheets makes collaborating easy, but managing hundreds of terms across dozens of languages quickly leads to broken lookup formulas, overwritten translations, and uncontrolled editing rights.
In a spreadsheet, one accidental paste can overwrite a master translation or wipe out a target language key across entire rows.
A dedicated database enforces strict types for language codes, workflow statuses, and linked records. A term connects directly to its localizations, pulling definitions through without fragile lookup formulas.
This is exactly what Softr Databases are designed for: keeping your localization data consistent, relational, and ready for production workflows.
Track translations across custom review stages like Draft, In Review, and Approved while preserving full audit visibility on who edited each entry.
Use Database AI agents to generate contextual usage examples for your translators and evaluate target translations directly inside the table.
You can also connect an existing Google Sheet if needed, but managing your glossary in a structured database gives your localization pipeline a scalable foundation.
Manage localization team members, roles, permissions, and edit logs
Track supported global language pairs and target translation mappings
Store technical glossary terms with definitions and AI usage examples
Track translated terms by language, approval status, and AI summaries
This database is built for cross-functional teams that need clean, aligned terminology across product, marketing, and global operations.
Customize your schema in minutes by adding custom categories, regional dialect tags, or character limits for mobile UI elements directly in your table settings.
Import your existing terminology using CSV uploads or sync your glossary with external developer tooling using the built-in database API.
When your localization pipeline grows, build an app on top of this database using the AI Co-Builder. You can prompt Softr to generate a dedicated translator portal with customized users and permissions, letting freelance translators submit copy without exposing the entire master term database.
A localization glossary database is a centralized system that stores approved source terms, definitions, and their verified translations across multiple languages. It ensures consistent terminology across software interfaces, documentation, and global marketing materials.
A no-code database provides relational integrity between master terms and language pairs without requiring complex database administration. It prevents accidental overwrites, maintains clean review statuses, and adapts instantly as you add new target markets.
Configurable Database AI agents can automatically generate realistic usage examples based on source definitions to assist translators. They can also analyze translated strings against contextual definitions to flag potential quality or tone mismatches automatically.
Yes, you can use the AI app generator to create a dedicated web portal on top of your glossary in seconds. You can set granular permissions so external translators only view and edit their assigned languages, while internal reviewers handle approvals.
Yes, this template is completely free to copy and use within Softr. Softr includes database features on the free plan with unlimited collaborators, and higher tiers offer larger record capacities for growing teams.
While Google Sheets works well for basic tabular lists, it lacks native relational links, role-based editing controls, and automated field-level AI workflows. This database maintains linked relationships between source terms and target languages without fragile formulas that break when rows shift.
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