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FrootAI — AmpliFAI your AI Ecosystem Get Started

All Solution Plays

Play 57

AI Translation Engine

High Designed

Context-aware multilingual translation with domain glossaries and quality scoring.

Real-time multilingual translation engine supporting 100+ languages with context-aware domain-specific glossaries. Combines Azure AI Translator for base translation with OpenAI for nuance, cultural adaptation, and quality scoring. Features human review queues for high-stakes content, batch processing pipelines, and CDN-backed delivery for global low-latency access.

Architecture Pattern

Hybrid translation: base translator + LLM refinement, quality gating

Azure Services

Azure OpenAIAzure AI TranslatorCosmos DBContainer AppsAzure CDN

DevKit (.github Agentic OS)

  • agent.md — root orchestrator with builder→reviewer→tuner handoffs
  • 3 agents — Translation Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
  • 3 skills — deploy (252 lines), evaluate (128 lines), tune (167 lines)
  • 4 prompts — /deploy, /test, /review, /evaluate with agent routing
  • .vscode/mcp.json — FrootAI MCP with Translator + OpenAI key inputs + envFile

TuneKit (AI Config)

  • config/openai.json — refinement and cultural adaptation
  • config/guardrails.json — quality thresholds, language coverage
  • evaluation/eval.py — BLEU >0.80, Quality gate >90%

Tuning Parameters

Quality score thresholdGlossary match priorityCultural adaptation levelBatch processing concurrencyHuman review trigger score

Machine evidence

FrootAI evidence lifecycle

This is an internal evidence maturity label, not third-party certification, accreditation, legal compliance, or a production guarantee. Missing or expired evidence demotes automatically; catalog claims cannot promote a play.

Designed
designed
build verified
evaluation verified

This play currently has design evidence only. A runnable scenario, endpoint evaluation, and build receipts are the next contiguous gates.

Loading architecture and cost model…

Repo Intelligence

v1

A no-clone, revision-pinned map for agents and humans. Observed evidence is separated from inferred flow so the output stays useful without pretending to be a full call graph.

Indexing bounded repository evidence…