Stable Diffusion

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SMB AI implementation starts from ¥20,000/month with ROI achievable in 3-6 months. This guide covers 5 implementation steps, automation effects by business function, and subsidy utilization.

**Open GENAI** (the OSS release of Japan's government generative-AI platform **源内 / GENAI**) was published by Japan's Digital Agency on **April 24, 2026 on GitHub under MIT license** ([official release](https://www.digital.go.jp/en/news/907c8e5d-2f4f-4bd7-9400-37c9f4221d7d) / [GENAI Web repo](https://github.com/digital-go-jp/genai-web) / [GENAI AI apps repo](https://github.com/digital-go-jp/genai-ai-api)). **What's released**: - **GENAI Web**: an AI interface built on TypeScript / React 19 / Zustand 5 / React Router 7 / AWS CDK / Tailwind CSS, with the **Digital Agency design system** - **GENAI AI Apps**: three development templates — **AWS for administrative RAG / Azure for self-hosted LLM / Google Cloud for a legal-system AI** referencing current statutes **License**: **MIT + CC BY 4.0** (commercial use, modification, and redistribution allowed) **Scale**: the foundation of a 2026-fiscal-year **pilot covering ~180,000 government employees across all ministries**, with planned expansion to local governments and private-sector adopters. **Design thesis**: **REST API-first + an ExApp (external-app integration) microservices model**, unifying AWS / Azure / Google Cloud behind a single interface. The goal is to **structurally eliminate vendor lock-in and duplicate development across agencies**. **vs GenU (AWS Generative AI Use Cases)**: where GenU leans into AWS managed services (Bedrock Agents / Knowledge Base / MCP), GENAI is **REST-API + ExApp-extensible**, adding **enterprise-grade governance** — team management with RBAC (System Admin / Team Admin / User), SAML multi-IdP, KMS CMEK, TTL data-retention policies, multi-layer WAF, Bedrock Inference Profiles. The trade-off: features like video generation, web extraction, and prompt optimization are **not built in** but delegated to external ExApps. **Validated models**: Claude Sonnet 4.6, Amazon Nova Lite. **[PLaMo 3.0 Prime](../columns/plamo-3-0-prime-pfn-japanese-llm-2026-06)** has also been selected as a trial model. **Caveat**: the Digital Agency explicitly states that **"permanent maintenance is not guaranteed and the OSS publication may be terminated in the future."** Long-term operations are the adopting organization's responsibility. **Fully-local community fork**: **[hirokawaguchi/open-genai](https://github.com/hirokawaguchi/open-genai)** (unofficial, experimental, MIT) swaps Cognito → **Keycloak (SAML)**, Bedrock → **OpenAI-compatible APIs (Ollama / vLLM / LM Studio)**, OpenSearch → **Qdrant**, DynamoDB → **SQLite**, Transcribe → **faster-whisper**, Bedrock image → **Stable Diffusion** — running the full GENAI stack on **a single Docker Compose command** with zero cloud dependency. Recommended Japanese model: **Qwen2.5**. Supports macOS Apple Silicon (Metal), Linux + NVIDIA (CUDA), and CPU-only. **Oflight's view**: combined with the trends covered in our [Local LLM June 2026 Update](../columns/local-llm-landscape-2026-june-update), Open GENAI is **the frontrunner generative-AI platform for Japanese municipalities and public-sector adopters** — now via two distinct paths (the official cloud-deployed release plus the hirokawaguchi/open-genai local-deployment fork). The column closes with three direct inquiry funnels for Open GENAI evaluation, custom implementation, and ongoing maintenance.