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✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

AI chatbot for WPML String Translation: explain translated UI strings

SleekAI reads WPML's icl_strings and icl_string_translations tables along with the language settings, so editors get straight answers about which UI strings are translated, pending, or missing. Bring your own OpenAI, Anthropic, Google, or OpenRouter key.

♾️ Lifetime License available

SleekAI chatbot for WPML String Translation

A chatbot that knows your WPML string state

WPML String Translation stores its data in dedicated tables, including wp_icl_strings for the source strings and wp_icl_string_translations for each translated variant. Language settings live in icl_sitepress_settings and per-domain mappings. SleekAI can be wired to read those values as data sources, so the bot's system message exposes which domains have how many strings, which language pairs have outstanding translations, and which strings were updated most recently.

That turns String Translation's grid view into a conversation. An editor asks how many checkout strings are still untranslated in French, the bot counts entries in wp_icl_string_translations with status not equal to complete and answers. A theme developer asks which gettext domain the welcome message lives under, the bot reads wp_icl_strings and points to the right context. None of that needs custom SQL and none of it leaks, because display conditions keep the editorial bot scoped to translators and admins.

Multibot lets a separate front-of-site bot run with no access to translation tables. Conversation logging captures every question with model and page URL, so the team can see which language pairs draw the most editorial questions and where the backlog actually is.

Workflow

How SleekAI plugs into WPML String Translation

1

Map the WPML tables

Use the SleekAI Wizard to map wp_icl_strings and wp_icl_string_translations into named variables, plus language and domain settings from icl_sitepress_settings. The bot reads them live at request time.
2

Scope by role

Set display conditions on user role and capability so the editorial bot only appears for translators and admins. A separate public bot under multibot runs without any access to the strings tables or backlog data.
3

Bring your own key

Plug in an OpenAI, Anthropic, Google, or OpenRouter key. Use a fast model for short string-status lookups and a stronger model for longer reviews of a translator's pending workload across multiple languages.
4

Review the logs

Open the conversation log to see which language pairs and domains attract the most editorial questions. Use the patterns to plan training for new translators or to refine which gettext domains get auto-translation budget.

Try it now

A typical WPML String Translation conversation

A translator clearing a backlog of untranslated UI strings before a multilingual product launch.

Comparison

Generic chatbot vs SleekAI for WPML String Translation

Generic chatbot

  • Doesn't know which gettext domains have a translation backlog
  • Can't count entries in wp_icl_string_translations by status
  • No view of which strings were updated most recently
  • Treats UI translation questions as generic Polylang or i18n advice
  • Can't be scoped to translators and admins via display conditions

SleekAI chatbot

  • Reads wp_icl_strings and wp_icl_string_translations
  • Counts pending strings per language and per domain
  • Surfaces the most recently updated translations
  • Display conditions keep the bot scoped to translators
  • Logs every editorial question inside WordPress

Features

What SleekAI gives you for WPML String Translation

Domain-aware lookups

The system message includes the gettext domain list and string counts per domain, so the bot tells you the welcome string lives under woocommerce or theme without anyone digging through the String Translation grid manually.

Backlog by language

Ask how many strings are pending in French or Spanish and the bot reads wp_icl_string_translations with status filters, returning real counts so the team can plan translator time against actual backlog volume.

Recent change feed

See which strings were updated today, which translator touched them, and which domain they sit in. Useful right after a theme or plugin update that adds new strings the team needs to triage promptly.

Use cases

Where teams use SleekAI for WPML String Translation

Pre-launch backlog clearance

Before a multilingual product launch, the editorial lead asks which strings are still pending in the launch locales. The bot returns counts per language, per domain, so translators know where to spend the day.

Theme update triage

After a theme push adds new gettext strings, a developer asks which new strings appeared today. The bot lists them by domain so the team knows what to register for translation under WPML's gettext capture.

Translator handoff

A freelance translator asks which strings under the woocommerce domain still need their language. The bot answers without granting them access to the full WordPress admin or the WPML grid.

The bigger picture

Why a plain-English layer over WPML strings pays off

WPML String Translation is the right tool for managing UI strings across many languages, and the editor grid does a fine job once you have it open. The friction is at the meta level. How big is the backlog in French this week.

Which gettext domain did the new theme just add fifty strings to. Where does the "Place order" string actually live so a translator can find it without scrolling. Are the November additions complete in German and Spanish but not in Italian, which would block the campaign.

Those are not translation-quality questions; they are inventory questions about which strings exist, which are pending, and which were just touched. SleekAI answers them by reading the same tables WPML writes to and exposing the counts as variables in the system prompt. The translator stays inside their workflow, the editorial lead stops opening four filter combinations to count rows, and the developer learns which domain a string belongs to before opening String Translation.

WPML still owns the translation workflow; SleekAI is the read layer that turns the grid into a conversation the whole team can have.

Questions

Common questions about SleekAI for WPML String Translation

Yes. WPML stores its strings in wp_icl_strings and translations in wp_icl_string_translations, both of which are queryable like any custom table. SleekAI can be configured to read counts and recent rows from those tables and expose them as variables in the system prompt, so the model answers with real backlog numbers instead of generic estimates.

 

By default, no. SleekAI is read-only against the WPML tables. The bot tells you what is missing and where it lives. If you want write actions, you can wire WPML's own translation hooks into a SleekAI tool with a capability check, but most teams keep the actual translation work inside the WPML String Translation editor for review.

 

It works with both. The base WPML plugin stores language and config data in icl_sitepress_settings and related options; the String Translation addon adds the strings tables. SleekAI can read any combination of those, so the bot can talk about both site-wide language settings and per-string status without separate setup.

 

Yes. The bot can match against the source string in wp_icl_strings using a fuzzy lookup that you wire as a SleekAI variable. Search for "add to cart" and the bot returns the matching entries with their gettext domain and translation status, even if the translator did not know the exact original wording.

 

Not unless you configure it that way. Display conditions on user role and capability keep the WPML String Translation bot scoped to translators and admins. A public chatbot you run on the same site is a separate bot under multibot with its own data sources, and it does not read the strings tables.

 

Yes. wp_icl_strings stores the gettext domain along with the string, so the bot can report counts per domain (theme, woocommerce, plugin-X). That is usually how editorial teams reason about backlogs, since one theme update often adds many strings under one domain at once.

 

It can read whatever you expose. WPML stores the auto-translate credit balance in a setting and updates it after each batch; SleekAI can read that value and tell an editor how many credits remain. Refilling and configuring engines still happens inside WPML's translation management screens for safety.

 

Yes. Each WordPress install has its own WPML database and its own SleekAI configuration. Staging often has fewer translated languages or a smaller string set; the staging bot can talk about that without leaking production backlog numbers. Conversation logs stay per environment, so the data sets do not mix.

 

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