01
Product context lives across GitHub, Slack, Notion, Figma, and your TMS — never in one place when translation starts.
Product localisation
Product localisation that keeps up with every release
Turn product changes, pull requests, and launch briefs into reviewed, release-ready translations with AI-assisted workflows and human approval built in.
Join the waitlistThe shift
Product strings change faster than localisation can follow
02
AI drafts miss UI constraints, glossary rules, and what actually changed in the pull request.
03
Translation work starts too late in the release cycle, so locales block launches or ship with gaps.
Overview
Product teams ship continuously. Localisation teams are left reconciling context across tools after the fact.
01
Pull product context from where work happens
Gather string changes, PR descriptions, Slack threads, and launch briefs so translators see why copy changed — not just the diff.
02
Generate drafts with your preferred LLM
Use OpenAI, Claude, Gemini, or another provider without locking your stack to one model vendor.
03
Apply glossary, tone, and UI constraints before review
Enforce terminology, character limits, and product voice before drafts reach human reviewers.
04
Route work to reviewers inside your existing workflow
Keep review assignments, approvals, and comments in the TMS your localisation team already uses.
How it works
From pull request to release-ready locales
Hyperlocalise connects product change signals to the review and sync workflow your team already runs.
01
GitHub PR
Detect changed strings and gather PR context
02
Product context
Pull briefs, glossaries, and UI constraints
03
AI translation draft
Generate locale drafts with your LLM
04
Human review
Route to reviewers in your TMS workflow
05
TMS sync
Push approved translations back
06
Release check
Flag unresolved locales before ship
Key capabilities
Built for product release velocity
05
Sync with your TMS instead of replacing it
Push approved strings to Crowdin, Lokalise, Phrase, Smartling, or another platform without a migration project.
06
Catch bad translations before production
Run release checks and regression gates so unresolved locales and quality issues surface before merge.
Why this is different
An AI-native layer across your product stack — not another TMS
Hyperlocalise is not here to replace your TMS. It adds a workflow layer that connects engineering change signals, LLM-assisted drafting, human review, and release confidence.
01TMS agnostic
02LLM agnostic
03Human-in-the-loop by design
04Context-aware from GitHub and product briefs
05Built for localisation operations at release speed
06Works across engineering, product, and localisation workflows
Example workflow
A new onboarding flow ships in Friday's release
A product manager merges a pull request with a redesigned onboarding flow. Hyperlocalise detects changed strings, gathers context from the PR and product brief, creates translation drafts for each target locale, checks glossary and tone rules, routes them to reviewers in the TMS, syncs approved translations back, and flags unresolved locales before the release train leaves the station.
Build your AI-native localisation workflow
Join the Hyperlocalise waitlist and see how your team can launch global product content faster without replacing your existing tools.