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Release notes for Localization OS, starting with the public launch. This page grows with every future release.

2026-08-31: Localization OS publicly launched#

Localization OS is now publicly available. Highlights of the product at launch:

  • Multi-agent LLM translation workflows: configurable pipelines of translate, quality-check, human review, TM-match, and external vendor steps, with conditional branching and bounded correction loops.
  • Translation memory: every approved translation is remembered and reused, including a TM-match step that fills and locks exact matches so the rest of the pipeline skips them.
  • Glossaries: a terminology authority of required and do-not-translate terms that is enforced in the output, not just suggested.
  • LLM-based LQA: quality scoring and rulebook checks that feed a workflow's branching and gates.
  • A post-editing CAT editor: inline review and correction for the slice of content that needs a human, with edits written back to translation memory.
  • Memory: a per-customer notebook of terminology decisions and style rules, some written by hand and some learned from corrections.
  • Key-based projects: continuous localization for software strings, with a change feed built for CI.
  • Connectors: push-model integrations with systems including Airtable, Jira, Strapi, Contentful, Shopify, HubSpot, Akeneo, and WordPress.
  • The Evaluations Lab: side-by-side comparison of translation setups, with statistics that refuse to call a winner when the evidence is thin.
  • Image localization (beta): detect text in an image, translate it through the ordinary pipeline, and re-render it in another language.
  • Vendors: first-class external translation and review vendors, with rate cards, an optional spend-approval gate, and a reject-and-rework loop.
  • Reports and content routing: cost, token, volume, and quality reporting over existing runs, and rules that place inbound content automatically.
  • Web and CLI parity: every feature ships on both the web UI and the CLI, with the API and MCP surfaces mirroring it where applicable, for automation and CI.
  • Self-hosted by design: Docker or plain Python, SQLite by default with optional PostgreSQL, and enterprise identity, audit, and encryption controls.