Smartcat?

NOT REALLYA prototype of the interface is possible, but the durable product depends on difficult systems beyond the UI. Build a safer adjacent workflow instead.

BUILD FIRST

A non-sensitive or read-only version of the core experience
A manual review step wherever correctness or trust matters
A narrow companion tool that removes a real piece of work

LEAVE FOR LATER

Regulated decisions, payments, or irreversible actions
Claims of correctness, compliance, or uptime that the MVP cannot support
Sensitive integrations until security, support, and auditability are ready

RESEARCH NOTES

What this tool actually does.

Checked 2026-09-06

Smartcat is a cloud-based, all-in-one AI translation management system (TMS) for enterprise localization. It combines AI machine translation (280+ languages), generative AI translation with terminology control, OCR for PDFs/images, and automated AI quality scoring. Core workflows include project creation, file upload (software strings, documents, websites), a CAT-like segment editor with translation memory, glossary enforcement, and embedded linguistic QA reviews. It also offers multimedia translation (video/audio transcription, subtitle embedding, AI voiceovers), a multilingual AI content generator, customizable project/workflow templates, and an AI procurement platform for sourcing freelance linguists. Integrations include API access, data warehouse connectivity, BI reports, SAML SSO, and development toolchain integrations for software localization. Security features prevent downloadin

SOURCES

RESEARCHED BUILD PROMPT

Give this to your coding agent.

Build a self-hosted web application inspired by Smartcat's core localization workflow: a translation management system where project managers upload source documents (Markdown, JSON, CSV, DOCX-as-text), translators work in a split-view CAT editor with translation memory suggestions and glossary term highlighting, and reviewers approve segments before export.

User-facing requirements:
1. Project creation with source language, target languages, and file upload.
2. Segment list view with source/target columns, status badges (pending / in-progress / needs-review / approved), and filters by status and language.
3. CAT editor: one segment at a time, translation memory fuzzy-match suggestions (>=70% similarity), glossary term highlighting, word/character counts, and auto-save as you type.
4. Review mode: approver can edit, comment, approve, or reject segments.
5. Export: produce translated files in original format (JSON key-value, CSV, Markdown) with placeholder protection — never translate {{variables}} or code spans.

Technical requirements:
- Backend: Node.js/Express or Python/FastAPI with SQLite/Postgres. Store projects, documents, segments, translations, translation memory entries, and glossary terms.
- Frontend: React or Vue with simple routing; clean utilitarian layout, no heavy component library required.
- Translation memory: score segment similarity via Levenshtein ratio or token-overlap; store source/target pairs keyed by language pair.
- Glossary: simple term table; highlight exact term matches in the source segment.
- Machine translation: optional, via a pluggable adapter (e.g., LibreTranslate API or a mock endpoint) so the demo works offline without API keys.
- Auth: optional single-user demo mode; document security trade-offs.

Implementation approach:
- Monorepo with server and client; use npm concurrently or a single Python server serving built static files.
- Include a seed script with sample glossary and TM data so the app demos well immediately.

Do not copy Smartcat's brand name, logo, marketing copy, or visual design. Choose a distinct name (e.g., 'Locabee') and build a minimal, functional UI.

Deliberately out of scope: freelancer marketplace/procurement, billing, video/audio transcription and voiceover, OCR, AI content generation, SSO/enterprise compliance, data warehouse/BI integration, multi-tenancy, and real-time collaborative editing.

The README must include: setup steps (install, seed data, run), a brief architecture diagram, how TM scoring works, how to add a new MT adapter, and important limitations (no concurrent editing lock, simple auth only, placeholder protection covers only common patterns, not production-grade).

Anchor the build to the distinctive Smartcat workflow: create project -> upload file -> segment extraction -> translate with TM/glossary assist -> review -> export back to original format.

Visit the official product page