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Agentsは、データ、ワークフロー、外部システムにまたがるマルチステップの作業をオーケストレーションします。また、チームはこれを使用して、カスタムエージェントを直接構築し、スケーリングすることもできます。 \u003C/p\u003E\n\u003Cp\u003E企業のチームは、AIエージェントのプロトタイプ作成から本番環境への展開へと移行しつつあります。現在、チームはビジネス機能全体でエージェントの効率と精度を測定したいと考えています。信頼できるガバナンスの効いた環境で、実験段階から実際のビジネス成果の推進へと移行するためです。\u003C/p\u003E\n\u003Cp\u003Eこうした背景から、エージェント開発者は、信頼性の高い構築、迅速な反復、そして自信を持って本番環境へリリースできるプラットフォームを必要としています。アカウント管理者は、スケーラブルなガードレールを必要としています。これには、すべてのチームで機能する支出管理、データ分離、ガバナンスが含まれます。 \u003C/p\u003E\n\u003Cp\u003ECortex Agentsは、エンタープライズエージェント開発のライフサイクル全体にわたる機能をサポートします。 \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cb\u003E構築：\u003C/b\u003EMCP経由で任意の外部ツールに接続し、Snowflakeの境界内にあるサンドボックスでコードを実行できるエージェントを構築する。\u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003Eスケーリング：\u003C/b\u003E使い慣れたSnowflakeの行アクセスポリシーを使用してテナントごとのデータ分離を適用しながら、何千人ものユーザーに対してエージェントをスケーリングする。 \u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003Eガバナンス：\u003C/b\u003E同じポリシーと、包括的な予算によるコスト管理を通じてガバナンスを適用する。 \u003C/li\u003E\n\u003Cli\u003E\u003Cb\u003Eイテレーション：\u003C/b\u003E評価フレームワークを用いて反復し、品質を継続的に改善する。 \u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003Eこれらは合わせて、企業がエージェントをパイロット版から本番環境へと大規模に移行するために必要なインフラストラクチャを構成します。これは、Snowflake Intelligenceを支えるのと同じ基盤であり、Snowflakeのセキュリティおよびガバナンス境界内で構築されたマネージドソリューションです。\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-4c6e1959a5","alignment":"left","layout":"card","quoteSourceName":"—Tony Leopold氏","quoteSourceTitle":"United Rentals、テクノロジーおよび戦略最高責任者","showQuoteIcon":false,"quote":"「Snowflake Intelligenceを活用することで、1,600拠点以上のチームが自然言語を用いて、アナリストに頼ることなく運用パフォーマンスをより深く理解し、リアルタイムのインサイトにアクセスできるようになりました。これにより、ガバナンスの効いた単一のデータソースに基づき、意思決定の迅速化とビジネス全体における一貫性の向上が実現しています。今後については、Cortex Codeを活用してAIエージェントの構築とスケールを進めていく予定です。これにより、売上の成長加速と車両稼働率の向上を図り、日々の業務運営をさらに進化させていきます」","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_2103539773":{"id":"blog-text-7d60a639c6","text":"\u003Ch2\u003E構築：あらゆるものに接続し、あらゆることを実行\u003C/h2\u003E\r\n\u003Cp\u003E何千人ものユーザーが、日常的にAIを利用してデータにクエリを実行しています。Jiraチケットの作成、Salesforceレコードの更新、分析の実行、チャートの生成などのアクションを起こすことは、より困難なステップです。これには、外部システムへの接続、コードの実行、そして、ドメイン知識を反復可能なワークフローへと変換することが必要になります。これまでは、カスタムのツール統合を記述し、インフラストラクチャを立ち上げ、それらすべてを自社で保守する必要がありました。この統合の負担により、多くのチームが本番環境への展開を延期していました。Snowflake Intelligenceは現在、MCPコネクタ、コード実行、スキルをネイティブに統合しています。これにより、質問に答え、エンタープライズシステム全体で実際のアクションを起こすエージェントを簡単に構築できるようになりました。\u003C/p\u003E\r\n\u003Ch3\u003EMCPコネクタ：外部データ統合の標準\u003C/h3\u003E\r\n\u003Cp\u003EModel Context Protocol（MCP）は、AIエージェントを外部のツールやサービスに接続するためのオープン標準として登場しました。Cortex Agentsは現在、\u003Cb\u003EMCPコネクタ（近日一般提供開始）\u003C/b\u003Eをサポートしています。これは、最小限の構成でエージェントをAtlassian（JiraおよびConfluence）、GitHub、Salesforce、Google Workspace、SlackなどのMCP互換サーバーに接続できるネイティブな統合レイヤーです。\u003C/p\u003E\r\n\u003Cp\u003Eセットアップは、標準化されたインターフェイスとわかりやすいパターンに従って行われます。営業オペレーションチームは、SalesforceとJiraのインスタンスを迅速に接続できます。そして、Cortex Agentsを活用したSnowflake Intelligenceのインターフェイスを通じて対話し、パイプラインの追跡、顧客レポートのアップロード、チケットの作成を自動的に行うことができます。\u003C/p\u003E\r\n\u003Cp\u003Eロール、権限付与、監査ログなど、Snowflakeオブジェクトに適用されるのと同じガバナンスモデルが外部MCPサーバーにも適用されるため、管理が簡素化されます。 \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-4ab0acb5aa","height":"1752","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--a48c5ea8-ae83-4560-8ff5-05efd1c47562/sales-agent-1.jpg?quality=85&preferwebp=true","alt":"sales-1","lazyEnabled":true,"width":"2978",":type":"snowflake-site/components/image"},"blog_text_1240375441":{"id":"blog-text-2a2daf9901","text":"\u003Cp\u003E\u003Csub\u003E図 1：MCPコネクタ：エンタープライズツールとのシームレスな統合\u003C/sub\u003E\u003C/p\u003E\n\u003Ch3\u003Eエージェントスキル：モジュール式で再利用可能なタスクパッケージ\u003C/h3\u003E\n\u003Cp\u003Eデータ検索のみを目的として構築されたエージェントは、質問に答えることしかできません。\u003Cb\u003Eエージェントスキル（近日一般提供開始）\u003C/b\u003Eを使用すると、ユーザーが一度定義してデプロイしたモジュール式パッケージを使用して、エージェントが反復可能なマルチステップのタスク（予測の実行、レポートの生成、ワークフローの実行など）を実行できるようになります。\u003C/p\u003E\n\u003Cp\u003E企業は、組織全体に分散している専門知識を、複数のチームで再利用できるスキルとしてコード化できるようになりました。たとえば、アナリティクスチームが構築した予測スキルを、運用、営業、マーケティングの各部門のエージェントがコードを複製することなく使用できます。 \u003C/p\u003E\n\u003Cp\u003E適切なスキルを備えたエージェントは、それらのタスクをオンデマンドで実行できます。これにより、従業員はより価値の高い業務に集中できるようになります。組織全体でより多くのスキルが提供され、共有されるにつれて、追加の開発作業なしでエージェントの能力が徐々に向上し、チーム全体の生産性向上が加速します。\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_574486512":{"id":"image-e0c071c492","height":"1608","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--2612935d-fe9b-4dc5-8f3f-83aad4a25805/sales-agent-2.jpg?quality=85&preferwebp=true","alt":"sales-2","lazyEnabled":true,"width":"2978",":type":"snowflake-site/components/image"},"blog_text_1984385433":{"id":"blog-text-49536016f1","text":"\u003Cp\u003E\u003Csub\u003E図 2：エージェントスキル：チーム間で再利用可能なワークフロー\u003C/sub\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_97098978":{"id":"quote-item-8c343d1193","alignment":"left","layout":"card","quoteSourceName":"—Priya Almelkar氏","quoteSourceTitle":"Wolfspeed、CIO","showQuoteIcon":false,"quote":"「Snowflakeは、当社の業務全般におけるAI活用において中核的な存在となっています。Snowflake Intelligenceの導入により、製造パフォーマンスの分析やインサイトの迅速な抽出が可能になりました。さらに、設備やプロセスの問題が発生する前に予兆を検知することもできています。すでに製造、品質管理、サプライチェーン、財務の各部門で数十のAIエージェントを展開しており、信頼できるデータや重要なナレッジへの迅速なアクセスを実現しました。これにより、業務効率が向上し、インサイト獲得までの時間が短縮されたことで、工場現場でのより素早いアクションが可能になっています。これは、私たちの事業運営とスケールのあり方を進化させる重要な一歩です」","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1070232528":{"id":"blog-text-b1dbc8135a","text":"\u003Ch3\u003Eコード実行ツール：すべてのエージェントにサンドボックス化されたPython環境を提供\u003C/h3\u003E\n\u003Cp\u003E一部のタスクでは、まだ存在しないコードが必要になります。これは、計画されたタスクに合わせて生成および実装されます。\u003Cb\u003Eコード実行ツール（近日パブリックプレビュー開始）\u003C/b\u003Eは、会話の一部としてコードを生成および実行するためのサンドボックス化されたPython環境をエージェントに提供します。開発者はこれを使用して、データを分析し、問題を解決し、PDFなどの形式でドキュメントを生成できます。\u003C/p\u003E\n\u003Cp\u003Eサンドボックスはセッションレベルの分離を強制するため、エージェントは現在の会話に渡されたデータ以外のデータにはアクセスできません。エージェントは、コード実行が適切なアプローチであるかどうかを判断し、それに応じて呼び出します。ユーザーが収益トレンドチャートを要求すると、エージェントはPythonを生成して実行し、追加の構成なしで視覚化を返します。\u003C/p\u003E\n\u003Cp\u003Eより高度なユースケースでは、サンドボックスを拡張できます。追加のPythonパッケージは、Snowflake内での使用が承認された厳選されたパッケージをホストするSnowflake Artifact Repositoryを通じて利用できます。ネットワークルールと外部アクセス統合を介して外部ネットワークアクセスを許可できるため、エージェントはAPIに到達し、外部ソースからデータを取得して、ダウンストリームシステムに結果をプッシュできます。\u003C/p\u003E\n\u003Cp\u003EスキルがPythonスクリプトを参照する場合、その実行はCode Execution Toolに依存します。これら2つの機能は連携して機能するように設計されています。組織はコードを実行するスキルのライブラリを構築でき、Code Execution Toolがランタイムを処理します。\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1180998959":{"id":"image-0592171bd3","height":"940","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--d54ab479-5b87-4993-83e3-717c8ae73bce/bash-3.png?quality=85&preferwebp=true","alt":"bash","lazyEnabled":true,"width":"1498",":type":"snowflake-site/components/image"},"blog_text_408169165":{"id":"blog-text-0a343056a5","text":"\u003Cp\u003E\u003Csub\u003E図 3：コード実行：すべてのエージェントにセキュアでオンデマンドのPythonを提供\u003C/sub\u003E\u003C/p\u003E\r\n\u003Ch2\u003Eスケーラビリティ：妥協することなくチーム全体に展開\u003C/h2\u003E\r\n\u003Cp\u003E1つのパイロットエージェントが成功すると、多くの場合、次のように展開を拡大するプレッシャーが生じます。これを5,000人の営業担当者全員に展開できるでしょうか。複数の営業地域で共有できるでしょうか。それらの答えは通常、1つのチームで機能するものと、大規模展開で機能するものとの間のギャップを浮き彫りにします。マルチテナント展開では、グループ間のデータ分離が必要です。更新のロールアウトには、本番環境を中断することなくテストを行う必要があります。歴史的に、どちらの問題も数週間にわたるカスタムエンジニアリングを必要としてきました。\u003C/p\u003E\r\n\u003Ch3\u003Eマルチテナント：1つのエージェント、多数のテナント、分離されたデータ\u003C/h3\u003E\r\n\u003Cp\u003E\u003Cb\u003Eマルチテナント（一般提供）\u003C/b\u003Eにより、単一のCortex Agentで複数のテナント（異なるチーム、リージョン、顧客など）にサービスを提供しながら、個別のエージェントインスタンスを展開することなく、テナント間の厳格なデータ分離を強制できます。\u003C/p\u003E\r\n\u003Cp\u003Eこのモデルでは、セッション属性と行アクセスポリシーを使用します。エージェントを呼び出す際、アプリケーションはセッションに永続化されるテナント固有の値を渡します。エージェントがSQLを実行する前に、これらの値はセッション属性として設定されます。テーブルの行アクセスポリシーはこれらの属性を参照して行をフィルタリングするため、地域の営業エージェントは、呼び出し元のアプリケーションが指定したリージョンのデータのみを表示できます。\u003C/p\u003E\r\n\u003Cp\u003ESnowflakeは不変のセッション属性をサポートしています。つまり、テナントコンテキストは一度設定されると、セッション中に生成されたSQL、コード実行、ツール呼び出しによって変更することはできません。悪意のあるクエリがテナントコンテキストを変更しようとした場合でも分離要件が維持されるように、Snowflakeでは行アクセスポリシーに不変のセッション属性を使用することを強くお勧めします。\u003C/p\u003E\r\n\u003Ch3\u003Eエージェントのバージョン管理：本番環境向けのライフサイクル管理\u003C/h3\u003E\r\n\u003Cp\u003E新しいアプリケーション構成によって本番環境で何かが破損した場合、問題となるのは「何が問題だったのか」ではなく、「どれだけ早くロールバックできるか」です。\u003Cb\u003Eエージェントのバージョン管理（一般提供）\u003C/b\u003Eは、開発と本番環境を分離するコミットベースのライフサイクルモデルを導入することで、この問題を解決します。\u003C/p\u003E\r\n\u003Cp\u003Eすべてのエージェントには\u003Cb\u003Eライブバージョン\u003C/b\u003E（開発用の変更可能な作業コピー）があり、ライブバージョンをコミットすることで作成される不変のスナップショットである\u003Cb\u003E名前付きバージョン\u003C/b\u003Eを任意の数だけ持つことができます。コミットにより、名前付きバージョンにはシステム割り当ての識別子（VERSION$1、VERSION$2など）が作成されます。名前付きバージョンは変更できません。その不変性が信頼性の高い展開の基盤となります。\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003Eエイリアス\u003C/b\u003Eは、名前付きバージョンに割り当てる、人間が読めるルーティングラベル（production、staging、canary）を提供します。あるバージョンから別のバージョンにエイリアスを再割り当てすると、呼び出し元のアプリケーションに変更を加えることなく、すべてのトラフィックがリダイレクトされます。新しいバージョンのプロモートは1行のコマンドで実行でき、ロールバックは前のバージョンを指す同じコマンドで実行できます。\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003EGitでエージェント構成\u003C/b\u003Eを管理しているチームは、ライブバージョンを完全にバイパスして、Git接続ステージから直接インポートすることで名前付きバージョンを作成できます。その結果、エンジニアがすでに知っているエージェント展開モデルが実現します。開発環境で構築し、ステージング環境でテストし、本番環境にプロモートして、必要に応じてロールバックします。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_585545919":{"id":"image-91db4f03ed","height":"806","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--fc0d4e71-0ee1-4877-98e3-c4abc1b82608/agent-versioning-4.png?quality=85&preferwebp=true","alt":"version","lazyEnabled":true,"width":"1502",":type":"snowflake-site/components/image"},"blog_text_344163520":{"id":"blog-text-e6c1701855","text":"\u003Cp\u003E\u003Csub\u003E図 4：エージェントのバージョン管理：即時ロールバックによる安全な展開\u003C/sub\u003E\u003C/p\u003E\n\u003Ch2\u003Eガバナンス：あらゆるレベルでコストを管理\u003C/h2\u003E\n\u003Cp\u003EAIエージェントの使用量は、消費されるクレジットに直結します。エージェントを広く展開する企業は、ほとんどのプラットフォームでまだ標準となっていない次のような質問に対する答えを必要としています。財務チームは共有アナリティクスエージェントにいくら費やしているでしょうか。チームが月間のbudgetを使い切った場合、どうなるでしょうか。アクセスは自動的に遮断されるのでしょうか。同じエージェントに対して、エンジニアリングチームの制限とは独立した制限を営業チームに設定できるでしょうか。包括的なコスト管理と使用状況の追跡により、チームはbudgetの超過を心配することなく、安心してAIを拡張できます。 \u003C/p\u003E\n\u003Ch3\u003Eリソースbudget：エージェントレベルの支出管理\u003C/h3\u003E\n\u003Cp\u003E\u003Cb\u003ECortex Agents向けのリソースbudget（一般提供）\u003C/b\u003Eは、Cortex Agentオブジェクトに月間クレジット支出上限を適用し、組織全体でタグベースのコスト帰属モデルを追跡します。チームレベルおよび組織全体のbudgetを設定して追跡できるため、支出が可視化され、管理され、使用状況に沿ったものになります。Snowflakeは、タグ付けされたエージェントのクレジット消費を追跡し、しきい値に達したときに設定されたアクションを実行します。\u003C/p\u003E\n\u003Cp\u003Eしきい値アクションのモデルは柔軟です。80%に達したら、チームリーダーにアラートを送信できます。100%で、ストアドプロシージャがアクセスを取り消します。制限を超えるニーズがあるチーム（たとえば、財務分析エージェントの決算期など）に対しては、100%を超えるしきい値で復元アクションを設定し、その後200%でハードストップを設定できます。サイクル開始アクションにより、新しいbudget期間の開始時にアクセスが自動的に復元されます。\u003C/p\u003E\n\u003Cp\u003Ebudgetにより、エンジニアリング、財務、およびその他のすべてのチームは、コンピュートやストレージに対してすでに持っているのと同じ管理をAI支出に対しても行えるようになります。エージェントの過剰な使用が、月末の請求で初めて発覚する、といった事態を防げます。\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1664246619":{"id":"image-af2a480521","height":"810","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--43bfbb83-ddb6-4212-a25c-023fb286f2e5/agent-budget-5.png?quality=85&preferwebp=true","alt":"agent-5","lazyEnabled":true,"width":"1472",":type":"snowflake-site/components/image"},"blog_text_1108969399":{"id":"blog-text-658f9196a7","text":"\u003Cp\u003E\u003Csub\u003E図 5：リソースbudget：エージェントの支出を正確に管理する\u003C/sub\u003E\u003C/p\u003E\r\n\u003Ch3\u003E共有リソースbudget：共有エージェントにおけるチームごとの支出\u003C/h3\u003E\r\n\u003Cp\u003Eリソースbudgetはエージェントレベルで機能します。つまり、どのチームが実行しているかに関係なく、そのエージェントのすべての使用に適用されます。\u003Cb\u003E共有リソースbudget（一般提供）\u003C/b\u003Eは、ユーザーグループのレベルで機能します。複数のチームが同じエージェントを共有しながら、各チームは独立した支出制限内で作業できます。budgetはチームレベルで適用されるため、各グループの使用状況は独立して追跡および管理されます。Snowflakeは、同じインスタンスを使用する他のグループとは独立して、共有リソースに対するタグ付けされたユーザーのクレジット消費を追跡します。\u003C/p\u003E\r\n\u003Cp\u003Eユーザーが複数のbudget（エージェントのリソースレベルのbudgetと、チームの共有リソースレベルのbudget）の対象となる場合、各budgetは独立して評価され、ユーザーは最初に達したしきい値によって停止されます。たとえば、500クレジットの共有budgetを使い切った財務チームは、エージェント全体が1,000クレジットのリソース制限に達していなくても、アクセスを失います。他のチームは影響を受けずに継続できます。\u003C/p\u003E\r\n\u003Cp\u003Eこのモデルにより、プラットフォームチームは共有インフラストラクチャを柔軟にデプロイできると同時に、個々のビジネスユニットは自身の消費を管理できるようになります。\u003C/p\u003E\r\n\u003Ch2\u003E反復：重要な点を測定し、問題が起きた箇所を修正する\u003C/h2\u003E\r\n\u003Cp\u003ELLMは本質的に非決定性を持ちます。ツールオーケストレーションは静かに失敗する可能性があります。エージェントがデータ検索でハルシネーションを起こしても、もっともらしい回答を生成することがあるためです。一般的な品質メトリクスでは、ドメイン固有のエラーを捉えることはできません。構造化された測定がなければ、チームはエージェントが時間の経過とともに改善しているのか悪化しているのかを判断できません。Cortex Agent Evaluationsを使用すると、セキュアなSnowflakeの境界内で直接、エージェント型アプリケーションを監視および反復できるようになりました。 \u003C/p\u003E\r\n\u003Ch3\u003ECortex Agent Evaluations：主観的なレビューから定量化されたパフォーマンスへ\u003C/h3\u003E\r\n\u003Cp\u003E\u003Cb\u003ECortex Agent Evaluations\u003C/b\u003Eが一般提供されました。このフレームワークを使用すると、テストクエリと期待されるエージェントの動作のデータセットを定義し、エージェントに対して評価を実行して、実行ごとに定量化されたメトリクスを受け取ることができます。\u003C/p\u003E\r\n\u003Cp\u003E評価は、\u003Ca href=\"https://www.snowflake.com/en/engineering-blog/ai-agent-evaluation-gpa-framework/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflakeのAgent GPA（Goal-Plan-Action）フレームワーク\u003C/a\u003Eによって強化されています。これは、3つの組み込みのメトリクスを提示する、研究に裏付けられたアプローチです。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003Eツールの選択と実行の精度：\u003C/b\u003Eエージェントは適切な段階で適切なツールを選択し、期待される入力と出力でそれらを正しく実行したでしょうか。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E回答の正確性：\u003C/b\u003Eエージェントの応答は期待される回答とどの程度一致していたでしょうか。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E論理的一貫性：\u003C/b\u003Eエージェントの指示、計画、およびツール呼び出しは内部的に一貫しているでしょうか。 \u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ETRAIL/GAIAベンチマークにおけるGPAフレームワークのパフォーマンスは、その信頼性を物語っています。ベンチマークテストでは、GPAの判定は人間が注釈を付けたエラーの95%を捉え（ベースラインは55%）、86%の精度で特定のトレーススパンにエラーを局所化しました。これは合格/不合格のシステムではありません。推論チェーンのどこでエージェントが破綻したかを正確に示します。\u003C/p\u003E\r\n\u003Cp\u003E実用的なメリットとして、チームは主観的な人間によるレビューから、構造化され、再現性のある品質の効果測定へと移行できます。最初の本番環境への展開前に、評価を実行してベースラインを確立します。構成を変更するたびに再度実行し、品質が維持されていることを確認します。 \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1632987958":{"id":"image-913c64d713","height":"770","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--df44c378-5a14-4386-a00f-62e38c52a53e/6-record.png?quality=85&preferwebp=true","alt":"6-record","lazyEnabled":true,"width":"1440",":type":"snowflake-site/components/image"},"blog_text_1875702684":{"id":"blog-text-c400d7a734","text":"\u003Cp\u003E\u003Csub\u003E図 6：Agent Evaluations：GPAによる測定、診断、改善\u003C/sub\u003E\u003C/p\u003E\n\u003Ch2\u003ESnowflakeを活用したインテリジェンスがもたらす未来の働き方\u003C/h2\u003E\n\u003Cp\u003E​​Snowflake Intelligenceは、企業に新しい働き方をもたらします。インサイトは単なる回答にとどまらず、ビジネス全体で実際のアクションを促進します。\u003C/p\u003E\n\u003Cp\u003Eそのエクスペリエンスの背後には、本番環境でAIを運用するためのあらゆる要件を満たすように設計されたフルマネージドプラットフォームがあります。エンタープライズツールへの接続性、セキュアなコード実行、データ分離を伴うマルチユーザーのスケーラビリティ、きめ細かいコストガバナンス、品質向上のための組み込みの評価機能などです。\u003C/p\u003E\n\u003Cp\u003Eこれらの機能は、AIを大規模に展開する際の最大の障壁を取り除きます。統合の複雑さを解消し、ガバナンスとコスト管理を確保して、信頼できる測定可能な成果の基盤を提供します。\u003C/p\u003E\n\u003Cp\u003ESnowflake Intelligenceは、このシステムの中心に位置しています。ユーザーは1つの場所で質問し、データを探索し、アクションを実行できます。その裏で、プラットフォームがデータ、ワークフロー、システムをセキュアに接続します。この統合により、企業は複数のツールをつなぎ合わせたり、ガバナンスを妥協したりすることなく、実験段階から実際のインパクトへと移行できます。\u003C/p\u003E\n\u003Cp\u003ESnowflake上で実行されるため、すべてのインタラクションは、ガバナンスが効いたデータ、既存のアクセス制御、統合されたポリシーに基づいています。チームはAIのためにガバナンスを再構築する必要はありません。すでに信頼しているものを拡張するだけです。\u003C/p\u003E\n\u003Cp\u003ESnowflake Intelligenceの核となるのは、パーソナルなワークエージェントとしての機能です。コンテキストを理解し、複雑な推論を支援し、ユーザーに代わってアクションを実行します。これにより、チームはより迅速に行動し、より効果的にコラボレーションして、最終的にはAIのスピードで業務を進めることができます。\u003C/p\u003E\n\u003Cp\u003ESnowflake Intelligenceは本番環境に対応しており、データを意思決定に、意思決定をアクションへと変えます。すでに信頼されているデータプラットフォーム上に構築され、セキュアかつ大規模に機能します。\u003C/p\u003E\n\u003Ch2\u003E使用を開始する\u003C/h2\u003E\n\u003Cp\u003Eこれらの機能は一般提供されています。詳しくは以下をご覧ください。 \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E最新の\u003Ca href=\"https://www.snowflake.com/ja/blog/snowflake-intelligence-work-agent/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Intelligenceのイノベーション\u003C/a\u003Eについてご覧ください。 \u003C/p\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/en/developers/guides/sfguide-getting-started-with-mcp-connectors/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eこちらのガイドを使用して\u003C/a\u003E、Snowflake IntelligenceでのMCPコネクタの利用を開始してください。\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E機能の詳細については\u003Ca href=\"https://docs.snowflake.com/ja/user-guide/snowflake-cortex/cortex-agents\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eドキュメントを参照\u003C/a\u003Eするか、\u003Ca href=\"https://www.snowflake.com/en/developers/guides/best-practices-to-building-cortex-agents/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eクイックスタートガイド\u003C/a\u003Eを使用して最初のCortex Agentを構築し、迅速に利用を開始できます。\u003C/li\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","quote_item","blog_text_2103539773","image","blog_text_1240375441","image_574486512","blog_text_1984385433","quote_item_97098978","blog_text_1070232528","image_1180998959","blog_text_408169165","image_585545919","blog_text_344163520","image_1664246619","blog_text_1108969399","image_1632987958","blog_text_1875702684"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{},"columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"author_chip":"aem-GridColumn aem-GridColumn--default--12"},"id":"container-c2de13066b","layout":"RESPONSIVE_GRID","columnCount":12,":type":"snowflake-site/components/container",":items":{"author_chip":{"id":"author-chip-434b336fbb","title":{"id":"title","type":"heading2","lines":["Learn more about the authors"],":type":"snowflake-site/components/title-v2"},"authors":[{"authorImage":{"id":"image-fea31217b6","height":"400","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--bab3c432-9d00-4fbb-9785-e632873b6c56/harshal.jpg?quality=85&preferwebp=true","alt":"Harshal 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