Efficiency
Less manual rebuild risk
Extracts translatable content, translates it through a controlled structure, and rebuilds usable assets without relying on repeated copy and paste work.
Translation AI / Governed Workflow
A controlled AI orchestration system for translating structured marketing assets while preserving layout, protected terminology, review states, and versioned audit evidence.
Workflow Evidence
The Translation AI build is framed around an operating workflow, not a loose prompt. Source assets, orchestration, language routing, QA gates, reviewed output, and archive evidence all need to be visible.
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Illustrative workflow panel for the governed Translation AI build.
Operational Value
Efficiency
Extracts translatable content, translates it through a controlled structure, and rebuilds usable assets without relying on repeated copy and paste work.
Quality
Product names, trademarks, merge fields, URLs, approved phrases, and restricted claims are protected before the model receives the payload.
Audit
Source asset, generated output, QA result, approval status, prompt version, and rules version can be stored against a version-controlled record.
Translation Controls
Translation AI is designed as an operating workflow, not a prompt window. The control layer separates approved source content, protected fields, translatable segments, machine output, QA results, and human approval so the translation process can be trusted.
Source
The approved source asset remains the baseline for comparison, rebuild, and rollback.
Rules
Names, links, placeholders, claims, tracking fields, and structural markers are isolated before translation.
Review
Generated output moves through QA and human review before it is treated as usable operational content.
Evidence
Prompt version, rules version, QA result, approved output, and rollback reference can be stored together.
Architecture
01
Source assets enter through a controlled upload route first, with future support for terminal, GitHub, and repository-triggered workflows.
02
A server-side orchestration route controls validation, payload construction, rules injection, model routing, QA coordination, and archive writes.
03
Language-specific translator profiles return structured segments. The builder layer reconstructs the translated asset without breaking layout or protected fields.
04
GitHub stores source, output, QA reports, prompts, and rules. Later retrieval can reuse approved phrases and rejected terms before each run.
Pipeline Flow
01
The system receives a structured marketing asset, validates the request, and identifies the asset type, source language, target language, and metadata.
02
The model receives structured JSON: segments, protected terms, formatting rules, glossary matches, prompt version, rules version, and output requirements.
03
The language router assigns the job to the right profile. The translator returns translated segments while preserving structure and controlled terms.
04
Automated checks validate protected terms, links, placeholders, structure, language target, and confidence score before human approval.
05
Source, generated output, approved output, QA report, prompt version, and rules version are stored so every job can be traced and recovered.
Language-Specific Translation Layer
Each target language can have its own translator profile, rules, approved phrasing, terminology behaviour, and quality controls. The orchestrator supervises every profile so no translator operates outside the governed workflow.
Governance Controls
> Cannot auto-approve translated assets
> Cannot bypass QA or human approval
> Cannot rewrite protected product claims
> Cannot store secrets in frontend code
> Source file and source commit
> Prompt version and rules version
> QA result and confidence score
> Approved asset and rollback reference
Technical Build Stack
Frontend
The interface remains replaceable. The durable value sits in the orchestration, payload, governance, QA, memory, and archive model.
Orchestration
Server-side orchestration keeps secrets out of the browser and gives the workflow a clean control point.
Model Layer
The model is a replaceable service. The durable value is the governed workflow wrapped around it.
Roadmap
V1
Upload source asset, build structured payload, translate through the orchestrator, rebuild output, run QA, download result, and archive evidence.
V2
Store approved phrase pairs, protected terms, rejected phrases, glossary rules, and language preferences for reuse before each translation run.
V3
A Git push from VS Code triggers the orchestrator through GitHub, then commits translated outputs and QA evidence back to the repository.
V4
Approved translated assets can be pushed into a controlled marketing platform work folder for human review before final placement.
V5
End-to-end translation, approval, deployment, rollback, reporting, and audit evidence through one governed workflow.
Signal
Use the contact form for demos, architecture conversations, speaking opportunities, or collaboration around governed AI translation workflows.