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Snowflake Intelligence는 바로 이 간극을 메웁니다.\u003C/p\u003E\n\u003Cp\u003E최신 업데이트를 통해 Snowflake Intelligence는 이제 모든 비즈니스 사용자를 위한 개인화된 업무 에이전트로 진화했습니다. 이 에이전트는 각 사용자가 데이터에 어떻게 액세스하고 인사이트를 도출하며, 기존에 사용하는 도구 전반에서 어떻게 실행으로 이어가는지를 학습합니다.\u003C/p\u003E\n\u003Cp\u003ESnowflake Intelligence는 비즈니스 사용자가 데이터 전반에 대해 질문하고 실행할 수 있는 단일 환경을 제공합니다. 이 개인화된 업무 에이전트는 비즈니스 컨텍스트에 기반한 결과를 생성하며, 사용자가 엔터프라이즈 데이터에 대한 공통된 이해를 형성하도록 지원합니다.\u003C/p\u003E\n\u003Cp\u003E비즈니스 사용자는 거버넌스가 적용된 통합을 통해 실제 업무가 이루어지는 시스템 전반에서 직접 작업을 수행할 수 있습니다. \u003Cb\u003EMCP 커넥터(GA 예정)\u003C/b\u003E는 Gmail, Google Calendar, Google Docs, Jira, Salesforce, Slack과 직접 연결되어 워크플로우를 벗어나지 않고도 실행할 수 있도록 지원합니다. 또한 새로운 Snowflake Intelligence\u003Cb\u003E iOS 모바일 앱(퍼블릭 프리뷰)\u003C/b\u003E과 응답 지연 시간에 대한 성능 개선을 통해서는 업무가 이루어지는 어디에서든 빠르고 사용 가능한 경험을 제공합니다. Cortex Agents 기반으로 구동되는 Snowflake Intelligence는 이미 엔터프라이즈 데이터를 저장하는 동일한 플랫폼 위에서 실행되며, 동일한 거버넌스 정책이 적용됩니다. 신뢰할 수 있고 거버넌스가 적용된 환경 내에서 실험 단계에서 실제 비즈니스 성과 창출로 전환할 수 있는 것입니다.\u003C/p\u003E\n\u003Cp\u003E이러한 새로운 기능을 바탕으로 Snowflake Intelligence는 읽기 전용 인사이트 중심 모델에서 실행 중심 모델로 전환되며, 에이전틱 엔터프라이즈를 위한 제어 영역을 구축하려는 Snowflake 전략의 핵심 기반을 형성합니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-26b657171d","alignment":"left","layout":"card","quoteSourceName":"Sameer Vuyyuru","quoteSourceTitle":"Chief AI and Product Officer, Capita","showQuoteIcon":false,"quote":"“Snowflake는 Capita의 AI Catalyst Stack을 뒷받침하는 데이터 및 인텔리전스 기반을 제공하여, 분산된 운영 데이터를 통합하고 당사가 운영하는 공공 서비스 컨택 센터와 혁신을 지원하는 민간 부문 컨택 센터 전반에 걸쳐 실시간 자연어 기반 인사이트를 제공합니다. Snowflake Intelligence를 통해 의사 결정을 가속화하고 운영 오버헤드를 줄이며 클라이언트 및 자체 운영 모두에서 의미 있는 효율성을 확보하고 있습니다. 또한 Snowflake는 성능, 규정 준수, 신뢰가 핵심인 고도로 규제된 공공 대상 서비스 환경 전반에서 적절한 거버넌스를 기반으로 AI를 안전하게 배포할 수 있도록 지원합니다.”","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_2098367194":{"id":"blog-text-94daea1401","text":"\u003Ch2\u003E엔터프라이즈 인텔리전스와 실행을 위한 단일 인터페이스\u003C/h2\u003E\n\u003Cp\u003E엔터프라이즈 규모에서 가장 어려운 문제는 인텔리전스 자체가 아닙니다. 핵심은 컨텍스트입니다. 에이전트가 실패하는 이유는 성능이 부족해서가 아니라, 비즈니스와 데이터, 그리고 각 조직의 상황을 충분히 이해하지 못하기 때문입니다. Snowflake Intelligence는 가장 중요한 데이터가 이미 존재하는 위치에서 동작하므로, 모든 답변은 조직이 정의한 의미와 시맨틱 모델을 기반으로 실제 비즈니스 상황에 근거합니다.\u003C/p\u003E\n\u003Cp\u003ESnowflake Intelligence는 전체 엔터프라이즈 데이터 자산 환경을 아우르는 단일 대화형 인터페이스를 제공합니다. 에이전트는 정보를 가져올 위치를 자동으로 판단합니다. Snowflake 테이블의 정형 데이터, 문서나 녹취록과 같은 비정형 콘텐츠, 또는 MCP 커넥터를 통해 연결된 외부 시스템까지 포함됩니다. 사용자는 시스템 구조나 데이터 위치를 알 필요가 없습니다. 질문만 하면 에이전트가 나머지를 처리합니다.\u003C/p\u003E\n\u003Cp\u003E예를 들어, 영업 리더가 주간 예측 검토를 준비하는 상황을 생각해 볼 수 있습니다. 현재 이 과정은 여러 대시보드를 열고, 보고서를 내보내며, 위험이 있는 거래를 수동으로 식별하는 것을 의미합니다. Snowflake Intelligence를 사용하면 이 모든 과정이 다음과 같이 하나의 대화로 이루어집니다.\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E“이번 분기에 성과가 지연될 가능성이 가장 높은 거래는 뭐지?”라는 질문을 받으면 에이전트는 파이프라인 데이터와 참여 추세를 분석해 모멘텀이 감소한 거래를 식별하며 그에 기여한 요인을 설명합니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E“위험도가 높은 상위 5개 계정에 대한 후속 조치를 작성해 줘.”에 대한 답변 과정에서 에이전트는 CRM 노트, 회의 요약, 계정 이력을 기반으로 개인화된 이메일을 생성합니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E“요약을 영업 채널에 게시해 줘.”라는 요청을 받게 되면 에이전트는 이를 \u003Cb\u003ESlack(GA 예정)\u003C/b\u003E으로 바로 전송합니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003E이전에는 CRM, 이메일 클라이언트, 분석가 간의 조율이 필요했던 작업이 이제 하나의 대화 안에서 몇 분 만에 이루어집니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-31883591b2","alt":"settings","lazyEnabled":true,":type":"snowflake-site/components/image"},"blog_text_1623808365":{"id":"blog-text-e974e8fdba","text":"\u003Cp\u003E\u003Csub\u003E자료 1: 시스템 전반에서 데이터 연결 및 작업 실행을 위한 MCP 커넥터\u003C/sub\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_158785934":{"id":"quote-item-0a45d8ac4f","alignment":"left","layout":"card","quoteSourceName":"Tony Leopold","quoteSourceTitle":"Chief Technology and Strategy Officer, United Rentals","showQuoteIcon":false,"quote":"“Snowflake Intelligence를 통해 1,600개 이상의 지점 전반에 있는 팀은 자연어를 사용해 운영 성과를 보다 잘 이해하고 분석가에 의존하지 않고도 실시간 인사이트에 액세스할 수 있습니다. 이는 의사 결정을 가속화하고, 거버넌스가 적용된 단일 데이터 소스를 기반으로 비즈니스 전반의 정렬을 강화하고 있습니다. 앞으로 Cortex Code는 매출 성장을 가속화하고 차량 및 장비 가용성을 개선하기 위해 AI 에이전트를 구축하고 확장할 수 있도록 지원하며, 일상적인 운영 방식을 발전시키고 있습니다.”","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1283653328":{"id":"blog-text-54613f298e","text":"\u003Ch2\u003E일상 워크플로우 전반에서 응답을 실행 결과로 전환\u003C/h2\u003E\r\n\u003Cp\u003E답변과 실행 결과의 차이는 조직 내 다양한 일상 업무 전반에 적용할 때 가장 명확하게 드러납니다.\u003C/p\u003E\r\n\u003Cp\u003E예를 들어, 재무 분석가가 예산 차이를 조사하는 상황을 생각해 볼 수 있습니다. 다음과 같이 “지난 분기 북동부 지역에서 운영 비용이 증가한 이유를 알려줘.”라고 요청을 하게 될 경우 에이전트는 비용 센터, 공급업체 인보이스, 기간 전반에 걸쳐 해당 차이를 추적한 후 다음을 수행합니다.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E특정 비용 요인 식별\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E항목별 세부 내역 제공\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E컨텍스트를 이해하기 쉬운 언어로 설명\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E이후 분석가는 에이전트에게 리더십 팀을 위한 요약을 생성하고 조달 팀에 알림을 보내도록 요청합니다. 두 작업 모두 몇 초 만에 완료되며 조사부터 커뮤니케이션까지 하나의 워크플로우에서 이루어집니다.\u003C/p\u003E\r\n\u003Cp\u003E인사이트는 시각화, 저장 및 공유가 가능하며 \u003Cb\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/ko/user-guide/snowflake-cortex/snowflake-intelligence/artifacts\"\u003EArtifacts\u003C/a\u003E(곧 GA 예정)\u003C/b\u003E 형태로 생성됩니다. Artifacts는 기반 데이터, SQL, 컨텍스트를 보존하는 재사용 가능하고 인터랙티브한 산출물로, Snowflake Intelligence 환경 내에서 분석 결과의 일관된 공유를 가능하게 합니다. 하나의 분석이 팀원들이 함께 구축하고 개선할 수 있는 살아 있는 공유 리소스로 발전하며, 거버넌스 제어는 그대로 유지됩니다.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1377547213":{"id":"image-3270151427","alt":"artifacts","lazyEnabled":true,":type":"snowflake-site/components/image"},"blog_text_1870563883":{"id":"blog-text-c6c59259e3","text":"\u003Cp\u003E\u003Csub\u003E자료 2: 답변을 결과로: 분석을 실행 가능한 공유 워크플로우로 전환\u003C/sub\u003E\u003C/p\u003E\n\u003Cp\u003E사용자는 \u003Cb\u003ESkill(GA 예정)\u003C/b\u003E로 이러한 워크플로우를 더 간소화할 수 있습니다. Skill은 반복 가능한 작업을 재사용 가능한 워크플로우로 전환하며, 사용자는 단일 프롬프트로 이를 실행할 수 있습니다. 고객 미팅 준비, 사용량 데이터 조회, 브리핑 생성과 같은 작업은 한 번 정의하면 단일 요청으로 실행할 수 있습니다. 주간 경영진 요약, 파이프라인 리스크 보고서, 회의 기록 기반 후속 조치 시퀀스는 자동화되어 팀 전반에서 공유할 수 있습니다.\u003C/p\u003E\n\u003Cp\u003E같은 패턴은 운영에도 적용됩니다. 운영 관리자가 “이번 주에 재고 리스크가 있을까?”라고 질문하면, 에이전트는 재고 수준, 공급업체 리드 타임, 물류 일정을 확인합니다. 특정 제품군에서 잠재적인 부족을 식별하고 근본 원인을 설명합니다. 이후 관리자는 다음과 같이 요청합니다.\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\"공급업체에 에스컬레이션해 줘.\" 실행 완료.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\"물류 팀용 Jira 티켓을 생성해 줘.\" 실행 완료.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003E이때 두 작업은 모두 거버넌스 경계 안에서 실행되며 시스템 간 수동 조율은 필요하지 않습니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_518770079":{"id":"image-92555decf0","alt":"jennifer","lazyEnabled":true,":type":"snowflake-site/components/image"},"blog_text_2146951734":{"id":"blog-text-2b5d7580bd","text":"\u003Cp\u003E\u003Csub\u003E자료 3: Skill: 인사이트에서 실행까지, 엔드투엔드 워크플로우 자동화\u003C/sub\u003E\u003C/p\u003E\r\n\u003Ch2\u003E거버넌스가 적용된 엔터프라이즈 데이터 기반\u003C/h2\u003E\r\n\u003Cp\u003E인사이트를 실행으로 연결하는 능력은 신뢰에 달려 있으며, 그 신뢰는 인텔리전스가 어디에서 작동하는지에서 비롯됩니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake Intelligence는 이미 엔터프라이즈 데이터가 저장된 동일한 플랫폼에서 직접 실행됩니다. 또한 역할 기반 액세스 제어, 행 수준 정책, 데이터 마스킹을 포함해 조직이 현재 사용하는 것과 동일한 거버넌스 모델을 적용합니다. 모든 응답은 사용자가 접근 권한을 가진 데이터를 기반으로 하며, 모든 실행은 관리자가 정의한 범위 내에서 이루어집니다. \u003Cb\u003E예산 제어 기능(GA)\u003C/b\u003E은 AI 사용에 대한 중앙 집중식 가시성을 제공하고, 팀 또는 워크플로우 수준에서 비용을 관리할 수 있도록 합니다. SCIM 기반 Okta 및 Microsoft Entra ID를 포함한 \u003Cb\u003E아이덴티티 공급자 통합(GA)\u003C/b\u003E을 통해 조직은 개별 Snowflake 계정을 수동으로 설정하지 않고도 비즈니스 사용자를 대규모로 프로비저닝할 수 있습니다. Snowflake Intelligence 전용 사용자는 Snowsight 또는 SQL 인터페이스에 대한 가시성 없이 인텔리전스 계층에 액세스하며, 자신의 역할에 맞는 사용 경험을 유지합니다.\u003C/p\u003E\r\n\u003Cp\u003E이는 범용 AI 도구와 비교할 때 의미 있는 차별점입니다. Snowflake Intelligence는 외부 시스템에 대한 거버넌스 기반 액세스와 엔터프라이즈 전체 데이터 자산에 대한 직접 액세스를 결합합니다. 모든 작업은 정의된 정책 내에서 실행됩니다. 모든 상호작용은 완전히 감사 가능하며, 이러한 감사 가능성이 AI를 실험 단계에서 프로덕션 환경으로 전환할 수 있게 합니다.\u003C/p\u003E\r\n\u003Ch2\u003EDeep Research를 통한 심층 분석\u003C/h2\u003E\r\n\u003Cp\u003E모든 질문이 단일 쿼리로 답변되는 것은 아닙니다. 일부 질문은 여러 시스템 전반의 신호를 연결해 하나의 데이터 세트만으로는 보이지 않는 관계를 드러내야 합니다.\u003C/p\u003E\r\n\u003Cp\u003EDeep Research(퍼블릭 프리뷰 예정)는 바로 이러한 시나리오를 위해 Snowflake Intelligence를 확장합니다. 데이터 사일로 전반에서 다단계 분석을 수행하고, 현재 발생 중인 사항, 그 원인, 후속 조치를 설명하는 구조화된 완전 인용 보고서 형태로 결과를 종합합니다. 일반적인 쿼리가 단일 응답을 반환하는 데 반해, Deep Research는 복수의 에이전트를 병렬로 실행하여 정형 데이터, 비정형 콘텐츠, 외부 컨텍스트를 함께 스캔하고, 통상적으로 여러 조직이 수일에 걸쳐 수행해야 하는 원인 규명이 필요한 복잡한 질문에 답합니다. 이는 \u003Cb\u003EExtended Thinking\u003C/b\u003E의 정밀한 단일 턴 심층 분석을 보완해 엔터프라이즈 전체 데이터 자산 전반에서 더 폭넓은 멀티소스 컨텍스트를 제공합니다.\u003C/p\u003E\r\n\u003Cp\u003E이탈을 분석하는 제품 팀은 특정 고객 세그먼트에서 예상 대비 높은 이탈률이 발생하는 원인을 질의합니다. Deep Research는 사용 데이터, 지원 티켓, 피드백 및 영업 상호작용을 동시에 분석하여 기여 요인을 중요도 순으로 식별하고 팀이 즉시 실행할 수 있는 권장 사항을 제공합니다.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_1088384042":{"id":"image-6350716041","alt":"performance","lazyEnabled":true,":type":"snowflake-site/components/image"},"blog_text_1658152357":{"id":"blog-text-d38be03fcb","text":"\u003Cp\u003E\u003Csub\u003E자료 4: Deep Research: 복합 원인 분석을 위한 멀티 에이전트 기반 크로스 소스 분석\u003C/sub\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item_698462063":{"id":"quote-item-c4e5163048","alignment":"left","layout":"card","quoteSourceName":"Kumar Maddali","quoteSourceTitle":"VP of Product Development, Telenav","showQuoteIcon":false,"quote":"“Snowflake Intelligence는 데이터에 신뢰할 수 있는 기반을 제공하고, Cortex Code는 데이터 활용 방식 전반에서 생산성을 크게 끌어올리고 있습니다. Telenav는 매월 20테라바이트 이상의 데이터와 하루 2억 건 이상의 이벤트를 처리합니다. 과거에는 가공 전 데이터에서 인사이트를 도출하는 데 수일에서 수주가 걸렸지만, 이제는 대화형 셀프서비스 환경을 통해 몇 분에서 몇 시간 내에 완료할 수 있습니다. 그 결과, 복잡한 데이터를 실시간 인텔리전스로 전환하고 비즈니스 전반에서 더 빠르고 더 정확한 의사 결정을 내릴 수 있게 되었습니다.”","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1386592820":{"id":"blog-text-71046bbfa3","text":"\u003Ch2\u003E모든 작업 환경에서 일관된 에이전트 접근성 제공\u003C/h2\u003E\n\u003Cp\u003E\u003Cb\u003ESnowflake Intelligence iOS 모바일 앱(퍼블릭 프리뷰)\u003C/b\u003E은 전체 Snowflake Intelligence 경험을 모든 디바이스로 확장하여, 사용자가 어디서든 인사이트를 기반으로 조치를 취하고, 권장 사항을 승인하며, 지속적인 목표를 확인할 수 있도록 합니다. Face ID 기반 인증은 로그인 마찰을 최소화하여, 간단한 확인만으로 즉시 개인 에이전트에 접근하고 이전 작업 상태를 그대로 이어갈 수 있도록 지원합니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image_497350668":{"id":"image-7701be9f6b","alt":"afternoon","lazyEnabled":true,":type":"snowflake-site/components/image"},"blog_text_1283510421":{"id":"blog-text-167ddce483","text":"\u003Cp\u003E\u003Csub\u003E자료 5: 전 환경에서 활용 가능한 에이전트: 모바일 기반 Snowflake Intelligence\u003C/sub\u003E\u003C/p\u003E\r\n\u003Ch2\u003E규모, 거버넌스, 빌더를 위해 설계\u003C/h2\u003E\r\n\u003Cp\u003E엔터프라이즈 전반에서 AI를 확장하려면 거버넌스 정책을 일관되게 적용하고, 지속적인 개선을 지원하며, 빌더에게 프로덕션 규모에서 필요한 도구를 제공하는 플랫폼이 필요합니다.\u003C/p\u003E\r\n\u003Cp\u003ECortex Agents는 그 기반을 제공합니다. 빌더는 조합 가능한 빌딩 블록을 활용해 워크플로우를 정의하고, 도구와 데이터 소스를 통합하며, 최종 사용자 경험을 구성하는 기능을 조립합니다. 이 플랫폼은 설계부터 배포, 모니터링까지 전체 수명 주기를 지원합니다. \u003Cb\u003EAgent Versioning(GA)\u003C/b\u003E과 CI/CD 워크플로우를 통해 팀은 안전하게 반복 개발을 수행하고 필요 시 롤백하며 프로덕션 소프트웨어와 동일한 엔지니어링 기준으로 변경 사항을 적용할 수 있습니다. \u003Cb\u003EAgent Evaluations\u003C/b\u003E는 각 단계에서 정확성과 신뢰성을 측정해 품질 개선이 필요한 시점을 명확히 제공합니다. \u003Cb\u003E안전한 코드 실행 샌드박스(퍼블릭 프리뷰 예정)\u003C/b\u003E는 에이전트 워크플로우 내에서 고급 데이터 변환, 통계 분석, 콘텐츠 생성을 지원합니다.\u003C/p\u003E\r\n\u003Ch2\u003E엔터프라이즈 AI를 위한 새로운 접근 방식\u003C/h2\u003E\r\n\u003Cp\u003E현재 9,100개 이상의 고객이 Snowflake의 AI 제품을 매주 사용하고 있으며, 엔터프라이즈가 AI 실험 단계를 넘어 실제 운영으로 전환함에 따라 그 수는 계속 증가하고 있습니다. \u003C/p\u003E\r\n\u003Cp\u003ESnowflake Intelligence는 기업이 이미 신뢰하는 기반 위에서 구축됩니다. 데이터를 외부 시스템으로 추출하는 대신 해당 기반에 직접 인텔리전스를 결합하는 것이 엔터프라이즈가 요구하는 규모와 신뢰 수준에서 AI를 실용적으로 만드는 핵심입니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake Intelligence는 이러한 비전이 오늘날 비즈니스 사용자에게 실제로 운영되는 영역이며, 모든 비즈니스 사용자에게 필요한 개인화된 업무 에이전트이자 에이전트 기반 엔터프라이즈를 위한 Snowflake 제어 영역의 기반입니다.\u003C/p\u003E\r\n\u003Ch2\u003E시작하기\u003C/h2\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca target=\"_blank\" href=\"https://www.youtube.com/watch?v=KGq9OXlWC1g\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Intelligence 데모\u003C/a\u003E를 시청하여 해당 기능이 실제로 작동하는 모습을 확인하세요.\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/ko/user-guide/snowflake-cortex/snowflake-intelligence/getting-started\"\u003E설명서\u003C/a\u003E를 활용해 Snowflake Intelligence를 시작해 보세요.\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/en/blog/enterprise-ai-agent-platform/\"\u003ECortex Agents\u003C/a\u003E를 통해 엔터프라이즈 AI 에이전트를 구축하고 거버넌스를 적용하며 확장하기에 Snowflake가 최적의 플랫폼인 이유를 알아보세요.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E\u003Csub\u003E미래 전망 진술\u003C/sub\u003E\u003C/p\u003E\r\n\u003Cp\u003E\u003Csub\u003E본 자료에는 향후 제품 제공 등에 대한 미래 전망 진술이 포함되어 있으나, 이는 어떠한 제품 제공에 대해서도 실제 제공을 보장하는 것은 아닙니다. 실제 결과와 제공 내용은 상이할 수 있으며, 이는 알려진 및 알려지지 않은 위험과 불확실성의 영향을 받을 수 있습니다. 보다 자세한 내용은 최신 10-Q를 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