/* ============================================================ NemakiWare — bilingual content dictionary window.CONTENT.en / window.CONTENT.ja ============================================================ */ window.CONTENT = { en: { nav: { features: "Why NemakiWare", architecture: "Architecture", mcp: "MCP & RAG", security: "Permissions", lineage: "Team Sharing", opensource: "Open Source", contact: "Contact", github: "GitHub", cta: "Contact us", }, hero: { eyebrow: "Open source · CMIS · RAG-ready", version: "v3.1", title_a_1: "The ", title_a_em: "permission-aware", title_a_2: " repository ", title_a_3: "that takes your AI into production.", title_b_1: "Permission-aware", title_b_2: "document infrastructure", title_b_3: "for the RAG era.", title_c: "Your LLM should only see what the user is allowed to see.", sub: "NemakiWare governs every document and every search result it produces with a single access-permission model — so the answers your AI returns never cross a line the user isn't allowed to cross.", sub_c: "NemakiWare is an open-source content repository where access control, AI search, and a connector for AI agents are one system — not three things bolted together.", cta1: "Talk to aegif", cta2: "View on GitHub", stat1_n: "1 ACL model", stat1_l: "from folder to vector result", stat2_n: "MCP built-in", stat2_l: "connect any AI agent", stat3_n: "AGPLv3", stat3_l: "fully open source", }, pains: { eyebrow: "Sound familiar?", items: [ "We want AI working on our internal documents — but the content underneath was never really managed.", "Sharing works today. But nobody can find what was shared a few months ago.", "Nobody knows how much of the older information may be disclosed — or to whom.", "Things get shared with individuals instead of roles, so every reorg leaves people stuck.", ], }, foundation: { eyebrow: "Why now", title: "AI only stands on a well-kept foundation.", body: "“Let AI read our internal documents and put them to work” — most companies share the ambition. But when the content underneath isn't managed, AI can't deliver. Built on a messy foundation, AI returns confidently messy answers.", points: [ { t: "No foundation for AI to read", d: "The content you want AI to use sits scattered and duplicated across systems, with no way to tell which version is the truth." }, { t: "Beyond team sharing, no control", d: "Teams and Slack work well for sharing within a team, within recent months. Content outside that scope — across teams, across time — is governed by no one." }, { t: "Unclear who may see what", d: "When the rules for who may see which document stay vague, AI inherits exactly that vagueness." }, ], }, shift: { eyebrow: "The RAG frontier", intro: "RAG — letting an AI read your own documents and answer from them — is where most enterprise AI projects begin.", title: "The proofs-of-concept work. Production is where they stall.", body: "Teams build impressive RAG demos on top of file shares, purpose-built vector databases, and even ordinary database-backed business systems. Then the rollout stops — because none of those foundations were built to answer one question reliably: is this particular person allowed to see this particular document? Access control was bolted on afterward, if at all. So the AI surfaces things people were never meant to see, and the project never goes live.", before_label: "The usual approach", before: [ "Documents copied into a separate search store", "Access rules re-implemented by hand — or skipped", "The AI can surface content a person isn't allowed to open", ], after_label: "With NemakiWare", after: [ "Documents and their search index live in one governed place", "One access-permission model, inherited automatically", "Every answer filtered by the asking person, in real time", ], }, pillars: { eyebrow: "Why NemakiWare", title: "Traditional document-management rigor, meets AI-native search.", sub: "Versioning, edit locking, custom metadata, fine-grained access permissions — everything a content repository has always done, now feeding an AI search layer filtered by those same permissions.", items: [ { t: "Permission-filtered AI search", d: "Meaning-based vector search results are checked against each person's access rights in real time. Hybrid keyword + semantic ranking, scoped to a folder tree when you need it." }, { t: "Automatic chunking & embedding", d: "Upload a PDF, Word, Excel, PowerPoint, HTML or text file and it is chunked, embedded and indexed — no extra pipeline to build or maintain." }, { t: "MCP server, built in", d: "Connect Claude, ChatGPT or any MCP-compatible agent straight to your repository over JSON-RPC. Five tools, governed by the same login." }, { t: "Bring your own embeddings", d: "Self-host Hugging Face TEI (multilingual-e5-large) or use Amazon Bedrock Titan V2 as a managed provider. Switch from the Setup Wizard." }, { t: "Full document lifecycle", d: "Versioning, relationships, retention, check-in/out, and archival to S3 cold storage with Legal Hold — the complete CMIS object model." }, { t: "Modern React UI", d: "Browse, search, manage users and groups, and configure every provider from a React 19 interface. A Setup Wizard runs on first launch." }, ], }, perm: { eyebrow: "The permission model", title: "Every result is checked before it is ever returned.", body: "Access control isn't a feature you switch on — it's the layer everything else sits on. Every document and folder carries a rule for who may see it (an ACL, based on the open CMIS standard), inherited down the folder tree and evaluated per person and per group on every request.", points: [ { t: "Access rules on every document", d: "Documents and folders carry a who-may-see-what list — the open standard, not a proprietary scheme." }, { t: "Inherited from parent folders", d: "Permissions cascade down the tree so structure and security stay in sync." }, { t: "User & group based", d: "Grant by individual or by group, backed by your directory of choice." }, { t: "Admin simulation mode", d: "“Search as user” lets an admin verify exactly what any person can — and cannot — see." }, ], flow_user: "Request from user", flow_q: "“quarterly revenue report”", flow_search: "Vector + keyword search", flow_acl: "ACL filter", flow_acl_d: "per-user, real time", flow_result: "Only permitted results", }, mcp: { eyebrow: "MCP & RAG", title: "Plug an AI agent straight into a governed repository.", sub: "NemakiWare exposes a Model Context Protocol server over JSON-RPC 2.0 (HTTP/SSE). Your agent authenticates once, then searches and retrieves — always inside the user's permissions.", tools_label: "MCP tools", tools: [ { n: "nemakiware_login", d: "Authenticate via username/password, API key, or OIDC" }, { n: "nemakiware_search", d: "Full-text keyword search" }, { n: "nemakiware_rag_search", d: "Semantic vector search" }, { n: "nemakiware_similar_documents", d: "Find related documents" }, { n: "nemakiware_get_document_content", d: "Retrieve document content" }, ], api_label: "REST · semantic search", providers_label: "Embedding providers", providers: [ { n: "Hugging Face TEI", t: "Self-hosted · default", d: "intfloat/multilingual-e5-large, 1024-dim. Ships as a Docker service." }, { n: "Amazon Bedrock", t: "Managed · Beta", d: "Titan Embedding V2 via IAM role or explicit credentials." }, ], }, lineage: { eyebrow: "Team sharing → lineage", betaNote: "Beta", title: "Pull content out of team-sharing silos — and connect it to your data lineage.", body: "Knowledge scattered across Slack, Box and cloud drives never makes it into governed retrieval. NemakiWare imports it into the repository, then links it onward to data-lineage catalogs — systems that track where information came from and how it travels — such as Apache Atlas and Microsoft Purview. A document's origin and journey stay visible end to end.", import_label: "Import from", import: ["Slack", "Box", "Google Drive", "OneDrive"], lineage_label: "Connect lineage to", lineageTargets: ["Apache Atlas", "Microsoft Purview"], mid: "NemakiWare repository", mid_d: "governed · ACL-aware · searchable", caption: "“Team sharing” paradigm content, imported and made governable — with lineage carried through. Available in beta.", }, cmis: { eyebrow: "Built on CMIS", title: "The standard that keeps you free.", body: "NemakiWare speaks CMIS — the open industry standard for content management — end to end. Any compatible client or business application connects without vendor lock-in, and the document operations you rely on are all standard.", items: [ "Access control", "Custom properties", "Full-text search", "Version control", "Check-in / check-out", "Relationships", "Retention & archival", "Sites & collaboration", ], bind_label: "Bindings", bindings: ["CMIS Browser Binding", "REST API v1", "MCP / JSON-RPC"], }, stack: { eyebrow: "Architecture", title: "A lean, modern stack you can run anywhere.", sub: "Docker Compose brings up the whole system; scale the pieces independently when you grow.", diagram: { agent: "AI Agent", agentSub: "MCP / REST", core: "NemakiWare", coreSub: "Tomcat 11 · Spring 7 · OpenCMIS", emb: "TEI / Bedrock", embSub: "embeddings", db: "CouchDB", dbSub: "documents", solr: "Solr", solrSub: "search + vectors", ui: "React UI", uiSub: "React 19 · Vite 7", }, stackTable: [ { k: "Server", v: "Tomcat 11 · Jakarta EE 11 · Virtual Threads" }, { k: "Framework", v: "Spring 7 · Apache Chemistry OpenCMIS" }, { k: "Database", v: "CouchDB 3.x" }, { k: "Search", v: "Apache Solr 9.x · full-text + DenseVector" }, { k: "UI", v: "React 19 · TypeScript · Vite 7 · Ant Design 5" }, { k: "Runtime", v: "Java 21" }, ], auth_label: "Authentication", auth: ["Password (BCrypt)", "WebAuthn / Passkey", "OIDC — Google, Microsoft", "SAML — Keycloak"], }, quick: { eyebrow: "Open source", title: "Up and running with Docker Compose.", sub: "Clone, build, and start the core services — CouchDB, Solr and NemakiWare — in a few commands. Add the embedding server with one profile flag.", steps: [ { n: "01", t: "Build the UI & server", c: "npm run build && mvn package" }, { n: "02", t: "Start core services", c: "docker compose up -d --build" }, { n: "03", t: "Open the React UI", c: "http://localhost:8080/core/ui/" }, ], ports_label: "Services", ports: [ { s: "NemakiWare", p: "8080", d: "Repository + React UI" }, { s: "CouchDB", p: "5984", d: "Document database" }, { s: "Solr", p: "8983", d: "Full-text & vector search" }, { s: "TEI", p: "8081", d: "Embedding server (rag profile)" }, ], license: "Licensed under AGPLv3 · © 2013–2026 aegif", }, contact: { eyebrow: "Get in touch", title: "Bring permission-aware AI retrieval to your content.", body: "aegif develops NemakiWare and provides professional support — installation, authentication-server integration, data import, administrator and user training, and consulting on content-oriented applications and ECM integration.", services: [ { t: "Annual support", d: "We investigate any issue and provide patches and workarounds." }, { t: "Initial setup", d: "Installation, auth-server connection and data import to get you productive in days." }, { t: "Training & consulting", d: "Administrator and user training, plus ECM integration advisory." }, ], cta: "Contact aegif", cta2: "Community site", }, footer: { tagline: "Permission-aware document repository for RAG.", community: "Community", product: "Product", company: "Company", links_product: ["Why NemakiWare", "Architecture", "MCP & RAG", "Permissions"], links_community: ["GitHub", "Community site", "Documentation", "Releases"], links_company: ["aegif", "Contact", "Privacy Policy"], rights: "© 2013–2026 aegif Corporation. All rights reserved.", etymology: "“Nemaki” comes from 寝巻き (pajamas) — relax and enjoy happy enterprise time.", }, }, ja: { nav: { features: "特長", architecture: "アーキテクチャ", mcp: "MCP & RAG", security: "権限モデル", lineage: "チーム共有", opensource: "オープンソース", contact: "お問い合わせ", github: "GitHub", cta: "お問い合わせ", }, hero: { eyebrow: "オープンソース · CMIS · RAG対応", version: "v3.1", title_a_1: "", title_a_em: "権限を理解する", title_a_2: "\nドキュメント基盤が", title_a_3: "\nAIを実運用へ進める", title_b_1: "RAG時代のための", title_b_2: "権限を理解する", title_b_3: "ドキュメント基盤", title_c: "AIに見せるのは\n許されたものだけ", sub: "すべての文書と、そこから生まれる検索結果を、ひとつのアクセス権ルールで統制。AIが返す答えが、その人に許されていない境界を越えることはありません。", sub_c: "NemakiWareは、アクセス権の管理・AIによる検索・AIエージェントとの接続が「ひとつのシステム」として動くオープンソースのコンテンツ基盤。後付けの三層ではありません。", cta1: "aegifに相談する", cta2: "GitHubで見る", stat1_n: "単一のアクセス権ルール", stat1_l: "フォルダから検索結果まで", stat2_n: "MCP内蔵", stat2_l: "あらゆるAIエージェントと接続", stat3_n: "AGPLv3", stat3_l: "完全なオープンソース", }, pains: { eyebrow: "こんな悩みをお持ちの方へ", items: [ "AIで社内の情報を活用したい。でも、土台になるコンテンツの管理ができていない。", "「今」の情報共有はできている。でも、数ヶ月前のものはわからない。", "古い情報をどこまで開示してよいのか、誰も知らない。", "役割ではなく個人あてに共有してしまうので、異動のたびに皆が困っている。", ], }, foundation: { eyebrow: "なぜ今", title: "AIは\n整備された基盤の上にしか自立できない", body: "「AIに社内の情報を読ませて活用したい」— 多くの企業が同じ構想を描きます。しかし土台となるコンテンツの管理が追いついていなければ、AIは期待した成果を出せません。乱れた土台の上では、AIも自信たっぷりに乱れた答えを返します。", points: [ { t: "AIに読ませる土台がない", d: "活用したいコンテンツがシステムごとに散在・重複し、どれが正なのか分からないままAIに渡されます。" }, { t: "チーム共有の「外」が統制不能", d: "TeamsやSlackで、チーム単位・直近数ヶ月の共有はうまく回っている。しかしそのスコープを外れたコンテンツ — チームをまたぎ、時間を越えた文書 — は、誰の管理下にもありません。" }, { t: "誰が見てよいかが曖昧", d: "「誰がどの文書を見てよいか」のルールが曖昧なままでは、その曖昧さをAIもそのまま引き継ぎます。" }, ], }, shift: { eyebrow: "RAGという最前線", intro: "RAG（社内の文書をAIに読ませ、その内容にもとづいて回答させる仕組み）は、多くの企業AIの出発点です。", title: "PoCは動く\nでも本番に進むには壁がある", body: "ファイル共有、専用のベクトルDB、さらには一般的なデータベース（RDB）上の業務システムの上に、印象的なRAGのデモが次々と作られます。ところが本番展開で止まる — どの土台も、「この人は、この文書を見てよいのか?」という問いに確実に答えるようには作られていないからです。アクセス権の制御は（あったとしても）後付け。結果としてAIは、本来見せてはならない情報まで提示してしまい、本番に出せません。", before_label: "よくあるやり方", before: [ "文書を別の検索ストアにコピー", "アクセス権を手作業で作り直す — あるいは省略", "利用者が開けない文書まで、AIが提示してしまう", ], after_label: "NemakiWareなら", after: [ "文書と検索インデックスが、統制された一つの場所に同居", "単一のアクセス権ルールが、自動的に継承される", "すべての回答を、質問した人の権限でリアルタイムにフィルタ", ], }, pillars: { eyebrow: "NemakiWareの価値", title: "伝統的な文書管理の厳格さと\nAIネイティブな検索の融合", sub: "バージョン管理、編集中のロック、独自の管理項目、きめ細かなアクセス権 — 文書管理基盤が担ってきたすべてが、権限でフィルタされたAI検索へとつながります。", items: [ { t: "権限でフィルタされるAI検索", d: "意味で探すベクトル検索の結果を、その人のアクセス権に対してリアルタイムに照合。キーワード検索とのハイブリッド、フォルダ単位の絞り込みにも対応します。" }, { t: "自動チャンク化と埋め込み", d: "PDF・Word・Excel・PowerPoint・HTML・テキストをアップロードするだけで、チャンク化・埋め込み・インデックスまで完了。追加のパイプラインは不要です。" }, { t: "MCPサーバーを内蔵", d: "Claude、ChatGPT、あらゆるMCP対応エージェントをJSON-RPCで直接リポジトリに接続。5つのツールが同一ログインの権限下で動作します。" }, { t: "埋め込みプロバイダは自由", d: "Hugging Face TEI（multilingual-e5-large）をセルフホスト、またはAmazon Bedrock Titan V2をマネージドで利用。セットアップウィザードから切替できます。" }, { t: "ドキュメントの完全なライフサイクル", d: "バージョン管理、リレーション、保持、チェックイン/アウト、リーガルホールド付きのS3コールドストレージへのアーカイブ — CMISオブジェクトモデルの全体を網羅。" }, { t: "モダンなReact UI", d: "閲覧・検索・ユーザー/グループ管理・各プロバイダ設定をReact 19のUIから。初回起動時にはセットアップウィザードが動作します。" }, ], }, perm: { eyebrow: "権限モデル", title: "答える前に\nすべての結果を必ず照合する", body: "アクセス権の制御は「オンにする機能」ではなく、他のすべてが乗る土台です。すべての文書とフォルダが「誰が見てよいか」のルール（国際標準CMISに基づくACL）を持ち、フォルダ階層に沿って継承され、すべてのリクエストで個人・グループ単位に評価されます。", points: [ { t: "すべての文書にアクセス権ルール", d: "文書とフォルダが「誰が見てよいか」のリストを保持。独自方式ではなく、オープンな標準に基づきます。" }, { t: "親フォルダから継承", d: "権限はツリーを下って継承され、構造とセキュリティが常に一致します。" }, { t: "ユーザー／グループ単位", d: "個人にもグループにも付与可能。任意のディレクトリと連携します。" }, { t: "管理者シミュレーション", d: "「ユーザーとして検索」で、特定の人物に何が見え・何が見えないかを管理者が正確に検証できます。" }, ], flow_user: "ユーザーからのリクエスト", flow_q: "「四半期の売上レポート」", flow_search: "ベクトル＋キーワード検索", flow_acl: "ACLフィルタ", flow_acl_d: "ユーザー単位・リアルタイム", flow_result: "許可された結果のみ", }, mcp: { eyebrow: "MCP & RAG", title: "統制されたリポジトリに\nAIエージェントを直結", sub: "NemakiWareはModel Context ProtocolサーバーをJSON-RPC 2.0（HTTP/SSE）で公開します。エージェントは一度認証すれば、常にユーザーの権限内で検索・取得を行えます。", tools_label: "MCPツール", tools: [ { n: "nemakiware_login", d: "ユーザー名/パスワード・APIキー・OIDCで認証" }, { n: "nemakiware_search", d: "全文キーワード検索" }, { n: "nemakiware_rag_search", d: "セマンティックベクトル検索" }, { n: "nemakiware_similar_documents", d: "関連ドキュメントの検索" }, { n: "nemakiware_get_document_content", d: "ドキュメント内容の取得" }, ], api_label: "REST · セマンティック検索", providers_label: "埋め込みプロバイダ", providers: [ { n: "Hugging Face TEI", t: "セルフホスト · 既定", d: "intfloat/multilingual-e5-large、1024次元。Dockerサービスとして同梱。" }, { n: "Amazon Bedrock", t: "マネージド · Beta", d: "Titan Embedding V2。IAMロールまたは明示的な認証情報で利用。" }, ], }, lineage: { eyebrow: "チーム共有 → リネージ", betaNote: "ベータ", title: "チーム共有のサイロを越えて\nデータの来歴までつなぐ", body: "Slack・Box・クラウドドライブに散らばった知識は、統制された検索の対象になりません。NemakiWareはそれをリポジトリに取り込み、さらにApache AtlasやMicrosoft Purviewといったデータリネージ（データの出自と来歴を追跡する仕組み）のカタログへ連携します。文書がどこから来てどう使われてきたかを、端から端まで見える状態に保ちます。", import_label: "インポート元", import: ["Slack", "Box", "Google Drive", "OneDrive"], lineage_label: "リネージ連携先", lineageTargets: ["Apache Atlas", "Microsoft Purview"], mid: "NemakiWare リポジトリ", mid_d: "統制 · ACL対応 · 検索可能", caption: "「チーム共有」パラダイムのコンテンツを取り込み、統制可能に。リネージも引き継ぎます。ベータ版で提供中。", }, cmis: { eyebrow: "CMIS準拠", title: "あなたを縛らない\n標準という選択", body: "NemakiWareは、コンテンツ管理のオープンな業界標準「CMIS」を端から端まで話します。CMISに対応したクライアントや業務アプリケーションは特定ベンダーへのロックインなく接続でき、日々使うドキュメント操作はすべて標準です。", items: [ "アクセス制御", "カスタムプロパティ", "全文検索", "バージョン管理", "チェックイン/アウト", "リレーション", "保持・アーカイブ", "サイト・コラボレーション", ], bind_label: "バインディング", bindings: ["CMIS Browser Binding", "REST API v1", "MCP / JSON-RPC"], }, stack: { eyebrow: "アーキテクチャ", title: "どこでも動く\n無駄のないモダンな構成", sub: "Docker Composeでシステム全体を起動。規模に応じて、各要素を独立してスケールできます。", diagram: { agent: "AIエージェント", agentSub: "MCP / REST", core: "NemakiWare", coreSub: "Tomcat 11 · Spring 7 · OpenCMIS", emb: "TEI / Bedrock", embSub: "埋め込み", db: "CouchDB", dbSub: "ドキュメント", solr: "Solr", solrSub: "検索＋ベクトル", ui: "React UI", uiSub: "React 19 · Vite 7", }, stackTable: [ { k: "サーバー", v: "Tomcat 11 · Jakarta EE 11 · 仮想スレッド" }, { k: "フレームワーク", v: "Spring 7 · Apache Chemistry OpenCMIS" }, { k: "データベース", v: "CouchDB 3.x" }, { k: "検索", v: "Apache Solr 9.x · 全文＋DenseVector" }, { k: "UI", v: "React 19 · TypeScript · Vite 7 · Ant Design 5" }, { k: "ランタイム", v: "Java 21" }, ], auth_label: "認証", auth: ["パスワード（BCrypt）", "WebAuthn / パスキー", "OIDC — Google, Microsoft", "SAML — Keycloak"], }, quick: { eyebrow: "オープンソース", title: "Docker Composeで\nすぐに起動", sub: "クローンしてビルドし、コアサービス（CouchDB・Solr・NemakiWare）を数コマンドで起動。埋め込みサーバーはプロファイル指定ひとつで追加できます。", steps: [ { n: "01", t: "UIとサーバーをビルド", c: "npm run build && mvn package" }, { n: "02", t: "コアサービスを起動", c: "docker compose up -d --build" }, { n: "03", t: "React UIを開く", c: "http://localhost:8080/core/ui/" }, ], ports_label: "サービス", ports: [ { s: "NemakiWare", p: "8080", d: "リポジトリ + React UI" }, { s: "CouchDB", p: "5984", d: "ドキュメントDB" }, { s: "Solr", p: "8983", d: "全文・ベクトル検索" }, { s: "TEI", p: "8081", d: "埋め込みサーバー（ragプロファイル）" }, ], license: "AGPLv3ライセンス · © 2013–2026 aegif", }, contact: { eyebrow: "お問い合わせ", title: "権限を理解するAI検索を\nあなたのコンテンツへ", body: "aegifはNemakiWareを開発し、プロフェッショナルなサポートを提供します。導入、認証サーバー連携、データインポート、管理者・ユーザー向けトレーニング、そしてコンテンツ指向アプリケーションやECM連携のコンサルティングまで。", services: [ { t: "年間サポート", d: "あらゆる問題を調査し、必要に応じてパッチや回避策を提供します。" }, { t: "初期導入支援", d: "導入・認証サーバー接続・データインポートで、数日のうちに使い始められる状態に。" }, { t: "トレーニング・コンサル", d: "管理者・ユーザー向けトレーニングと、ECM連携のアドバイザリ。" }, ], cta: "aegifに問い合わせる", cta2: "コミュニティサイト", }, footer: { tagline: "RAGのための、権限を理解するドキュメントリポジトリ。", community: "コミュニティ", product: "プロダクト", company: "会社", links_product: ["NemakiWareの価値", "アーキテクチャ", "MCP & RAG", "権限モデル"], links_community: ["GitHub", "コミュニティサイト", "ドキュメント", "リリース"], links_company: ["aegif", "お問い合わせ", "プライバシーポリシー"], rights: "© 2013–2026 aegif Corporation. All Rights Reserved.", etymology: "「ネマキ」は寝巻きから。ソファに寝転ぶように、快適なエンタープライズ体験を。", }, }, };