Developing Enterprise Frontier Safeguards with our customers与客户共同开发企业前沿安全防护措施
Today we’re announcing Enterprise Frontier Safeguards (EFS), a solution that combines the privacy of zero data retention (ZDR) with state-of-the-art safeguards for detecting misuse. EFS works by storing data in cloud infrastructure controlled by the customer, not Anthropic. EFS will be rolling out to customers in phases, starting later this fall. To make the transition smooth, eligible customers will receive ZDR on Fable 5 and Fable 5.1 until EFS is ready.今天，我们宣布推出企业前沿安全防护（Enterprise Frontier Safeguards，简称 EFS）。该解决方案将零数据留存（ZDR）的隐私性与用于检测滥用的尖端安全防护措施相结合。EFS 的工作原理是将数据存储在由客户而非 Anthropic 控制的云基础设施中。EFS 将从今年秋季晚些时候开始分阶段向客户推出。为确保平稳过渡，符合条件的客户在 EFS 就绪之前，可在 Fable 5 和 Fable 5.1 上使用零数据留存（ZDR）服务。
We developed EFS in close collaboration with more than 100 customers in industries like financial services, healthcare, manufacturing, telecom, law, retail, and the public sector, and with our cloud partners at Amazon Web Services, Google Cloud, and Microsoft Azure.我们在开发 EFS 时，与金融服务、医疗保健、制造业、电信、法律、零售和公共部门等行业的 100 多家客户，以及亚马逊云科技（AWS）、Google Cloud 和微软 Azure 的云合作伙伴进行了密切合作。
EFS will be supported on Claude Code, Claude Enterprise, the Claude Platform, Amazon Bedrock, Claude Platform on AWS, Google’s Agent Platform, and Microsoft Foundry.EFS 将在 Claude Code、Claude Enterprise、Claude Platform、Amazon Bedrock、AWS 上的 Claude Platform、Google Agent Platform 以及 Microsoft Foundry 上提供支持。
Solving the dilemma of frontier security解决前沿安全困境
Mythos-class models, like Claude Fable 5.1, represent a major increase in intelligence and agentic capabilities. However, with that increase comes the potential for both misuse and autonomous misbehavior.像 Claude Fable 5.1 这样的 Mythos 级模型代表了智能和智能体能力的重大提升。然而，随着能力的提升，滥用和自主不当行为的风险也随之增加。
Over the last few months, we’ve seen substantial evidence of attempted misuse of AI models. These range from typical forms of abuse, such as fraud, to sophisticated cyberattacks, which can include agents autonomously engaging in destructive behavior. Some of these instances involve theft or misappropriation of enterprise customers’ credentials, which are difficult to detect without the ability to monitor traffic and detect abnormal behavior.在过去几个月里，我们看到了大量试图滥用 AI 模型的证据。这些滥用行为范围广泛，从欺诈等典型滥用形式，到包括智能体自主进行破坏性行为在内的复杂网络攻击。其中一些案例涉及窃取或挪用企业客户的凭据，若没有监控流量和检测异常行为的能力，这些行为很难被发现。
Furthermore, because the most sophisticated misuse can involve many tasks spread across multiple sessions and accounts, it is not sufficient to run automated analysis on each interaction separately and then instantaneously discard the data. Effective detection requires storing data for a meaningful period of time so that it can be correlated across time and accounts.此外，由于最复杂的滥用行为可能涉及跨多个会话和账户的多个任务，仅对每次交互进行单独的自动化分析并立即丢弃数据是不够的。有效的检测需要将数据存储一段有意义的时间，以便能够跨时间和账户进行关联分析。
For this reason, we introduced 30-day data retention starting with Fable 5. This policy was not motivated by a desire to train on enterprise data: Anthropic has never trained on enterprise data without explicit permission, and never will.因此，我们从 Fable 5 开始引入了 30 天的数据留存政策。此政策并非出于利用企业数据进行训练的目的：Anthropic 从未在未经明确许可的情况下使用企业数据进行训练，未来也绝不会这样做。
The enterprises we worked with generally understood the safety and security value of data retention, but many–especially in regulated industries–found it difficult to use models with data retention. We therefore sat down with customers to design a solution that could provide the best of both worlds: the privacy of ZDR and the safety allowed by monitoring across time and accounts.我们合作的企业普遍理解数据留存对安全和保障的价值，但许多企业（尤其是在受监管行业）发现很难使用带有数据留存的模型。因此，我们与客户共同设计了一套解决方案，旨在兼顾两者的优势：既拥有 ZDR 的隐私性，又能实现跨时间和账户监控所带来的安全性。
Designed with our customers与客户共同设计
We built Enterprise Frontier Safeguards with feedback from the experts who will use it every day: security, product, compliance, and delivery teams. One of the groups we worked with was the Analysis and Resilience Center for Systemic Risk (ARC), whose members include the chief information security officers of the largest US banks, including Goldman Sachs, Morgan Stanley, Citi, Bank of America, and Wells Fargo. 我们在构建企业前沿安全防护（EFS）时，参考了每天都会使用它的专家——安全、产品、合规和交付团队的反馈。我们合作的团队之一是系统性风险分析与弹性中心（ARC），其成员包括美国各大银行的首席信息安全官，包括高盛（Goldman Sachs）、摩根士丹利（Morgan Stanley）、花旗（Citi）、美国银行（Bank of America）和富国银行（Wells Fargo）。
We also worked with leaders at companies such as Comcast, KPMG, Mastercard, Salesforce, and Visa, to make sure the design held up across industries. Our conversations spanned a quarter of the Fortune 100, every US global systemically important bank, and virtually every regulated industry.我们还与康卡斯特（Comcast）、毕马威（KPMG）、万事达卡（Mastercard）、Salesforce 和 Visa 等公司的领导者合作，确保该设计能够适应各行各业。我们的交流对象涵盖了财富 100 强企业中的四分之一、美国所有具有系统重要性的全球银行，以及几乎所有受监管的行业。
Here is what we heard from this wide range of customers, and what we built into EFS to address these common concerns:以下是我们从这些广泛的客户群中听到的反馈，以及我们为解决这些共同关切而内置于 EFS 中的功能：
On monitoring关于监控
Enterprises have long applied monitoring for insider risk, and now want help upleveling monitoring for agents. Their concerns were about Anthropic’s automated monitoring systems meeting their regulatory standards.企业长期以来一直将监控应用于内部风险管理，现在他们希望在提升智能体监控方面获得帮助。他们的担忧在于 Anthropic 的自动化监控系统是否符合他们的监管标准。
With EFS, customers control how data gets reviewed. When monitoring detects a pattern that needs attention, those signals are sent directly to customers so they can review what the automated systems detected.通过 EFS，客户可以控制数据的审查方式。当监控检测到需要关注的模式时，这些信号会直接发送给客户，以便他们审查自动化系统所检测到的内容。
On data storage关于数据存储
It’s a lot of work for enterprises to add another “trusted data vendor” for a number of reasons. They need to notify all of their customers who these vendors are and update contracts. They also have internal requirements for safely storing and auditing data, given its high level of sensitivity. Because of these concerns, we architected EFS so that customers have the ability to store data on their existing cloud infrastructure.由于多种原因，企业增加一个新的“受信任数据供应商”需要投入大量工作。他们需要通知所有客户这些供应商是谁并更新合同。鉴于数据的敏感性极高，他们还有内部关于安全存储和审计数据的要求。考虑到这些顾虑，我们对 EFS 进行了架构设计，使客户能够将数据存储在他们现有的云基础设施中。
In EFS, customers can control their data storage and management. Customers want the ability to have their data live in infrastructure they control, under their own encryption keys, access policies, and audit logging. Activity data used for monitoring can be stored in the customer’s own cloud account (such as Amazon S3, Azure Blob Storage, or Google Cloud Storage).在 EFS 中，客户可以控制其数据存储和管理。客户希望能够将数据存放在他们自己控制的基础设施中，并使用自己的加密密钥、访问策略和审计日志。用于监控的活动数据可以存储在客户自己的云账户中（例如 Amazon S3、Azure Blob Storage 或 Google Cloud Storage）。
On automated and human review关于自动化与人工审查
Even as automated review is becoming more effective, a person looking at a flag still adds value by confirming real misuse and clearing false positives. But what we heard from many customers, especially those in regulated industries, is that the person doing that review needs to be one of their own. Many operate under rules that tightly govern who may see certain information—privileged legal material, non-public information, drug-safety reports. Their teams are already trained and cleared for that work.即使自动化审查正变得越来越有效，人工查看标记内容仍然具有价值，可以确认真实的滥用行为并清除误报。但我们从许多客户（尤其是受监管行业）那里了解到，进行审查的人员必须是他们自己的员工。许多机构在严格的规则下运作，规定了谁可以查看特定信息——例如受法律特权保护的材料、非公开信息、药物安全报告等。他们的团队已经接受过相关培训并获得了相应授权。
EFS has automated safety monitoring, no Anthropic human review required. Customers want protection against cyberattacks, and appreciate that these can be difficult to detect if they unfold across many sessions and accounts. With EFS, automated systems analyze a rolling window of traffic for signals of serious misuse, including attempts to develop offensive cyber or biological capabilities and signs of stolen or leaked credentials. Those flags go directly to the customer and their people take it from there – no human review by Anthropic employees is required.EFS 具有自动化安全监控功能，无需 Anthropic 人工参与审查。客户希望抵御网络攻击，并意识到如果攻击跨越多个会话和账户，往往很难被发现。通过 EFS，自动化系统会分析滚动窗口内的流量，以寻找严重滥用的信号，包括试图开发攻击性网络或生物能力的行为，以及被盗或泄露凭据的迹象。这些标记会直接发送给客户，由他们的人员进行后续处理——无需 Anthropic 员工进行任何人工审查。
AI controls need to be designed to protect sensitive information, and model safeguards are an important part of that process. Anthropic engaged us as they developed Enterprise Frontier Safeguards to ensure alignment with our requirements and standards.AI 控制措施的设计需要保护敏感信息，而模型安全防护是该过程的重要组成部分。Anthropic 在开发企业前沿安全防护（EFS）时与我们进行了接触，以确保其符合我们的要求和标准。AI 控制措施的设计需要保护敏感信息，而模型安全防护是该过程的重要组成部分。Anthropic 在开发企业前沿安全防护（EFS）时与我们进行了接触，以确保其符合我们的要求和标准。Matt Chung，首席信息安全官兼技术风险主管
Enterprise Frontier Safeguards gives us exactly what we asked for: our logs stay in a Wells-managed environment under Wells-managed keys. We keep custody of our data while Anthropic operates the detection. That split is what lets our teams put frontier models to work safely and meet our obligations to customers, employees, and regulators. We helped shape these safeguards because our industry needs them.企业前沿安全防护（EFS）完全满足了我们的要求：我们的日志保留在富国银行管理的环境中，并使用富国银行管理的密钥。我们保留了对数据的监管权，而 Anthropic 则负责运行检测。这种分离使我们的团队能够安全地利用前沿模型，并履行我们对客户、员工和监管机构的义务。我们协助塑造了这些安全防护措施，因为我们的行业需要它们。企业前沿安全防护（EFS）完全满足了我们的要求：我们的日志保留在富国银行管理的环境中，并使用富国银行管理的密钥。我们保留了对数据的监管权，而 Anthropic 则负责运行检测。这种分离使我们的团队能够安全地利用前沿模型，并履行我们对客户、员工和监管机构的义务。我们协助塑造了这些安全防护措施，因为我们的行业需要它们。Munish Kumar Sharma，首席信息安全官
As a company that runs critical infrastructure, the capability of models is important. Just as important are solutions that allow us to keep our data in our own account, and Enterprise Frontier Safeguards settled it.作为一家运营关键基础设施的公司，模型的能力非常重要。同样重要的是那些允许我们将数据保留在自己账户中的解决方案，而企业前沿安全防护（EFS）解决了这个问题。作为一家运营关键基础设施的公司，模型的能力非常重要。同样重要的是那些允许我们将数据保留在自己账户中的解决方案，而企业前沿安全防护（EFS）解决了这个问题。Noopur Davis，执行副总裁、首席信息安全与产品隐私官
Eight of our members worked with Anthropic to define what it would take to run the most capable frontier models inside a systemically important bank: who holds the data, who holds the keys, what automated review can and cannot see, and under what conditions a human is ever permitted to look. This collaboration is leading to the development and delivery of improved safeguards and standards that could scale across our industry and beyond.我们的八名成员与 Anthropic 合作，定义了在具有系统重要性的银行内部运行最强前沿模型所需的条件：谁持有数据、谁持有密钥、自动化审查能看到什么以及不能看到什么，以及在什么条件下才允许人工查看。这种合作正在推动改进安全防护措施和标准的开发与交付，这些措施和标准有望在我们的行业乃至更广泛的领域推广。我们的八名成员与 Anthropic 合作，定义了在具有系统重要性的银行内部运行最强前沿模型所需的条件：谁持有数据、谁持有密钥、自动化审查能看到什么以及不能看到什么，以及在什么条件下才允许人工查看。这种合作正在推动改进安全防护措施和标准的开发与交付，这些措施和标准有望在我们的行业乃至更广泛的领域推广。Scott DePasquale，总裁兼首席执行官
One of the key tenets of the safeguards architecture is the ability for us to retain data and have it held outside the model itself, protected within our environment. There are areas of the firm, and of our clients' work, that are regulated and highly sensitive. Those safeguards actually allow us to apply AI in parts of the business that we wouldn't have been able to before.安全防护架构的关键原则之一是我们能够保留数据，并将其存放在模型本身之外，在我们自己的环境中受到保护。公司内部以及客户工作中存在一些受监管且高度敏感的领域。这些安全防护措施实际上使我们能够在以前无法涉足的业务领域应用 AI。服务合伙人 Todd Lohr，客户与市场全国管理合伙人
Service Partner安全防护架构的关键原则之一是我们能够保留数据，并将其存放在模型本身之外，在我们自己的环境中受到保护。存在一些受监管且高度敏感的领域。这些安全防护措施实际上使我们能够在以前无法涉足的业务领域应用 AI。服务合伙人
Our customers have trusted us with their data for more than two decades. That experience is exactly why we wanted to help think this through with Anthropic, rather than wait on the sidelines. We were able to work together on new security and privacy capabilities at the architecture level, not just the policy level.二十多年来，我们的客户一直信任我们将数据交给我们。正是基于这种经验，我们希望与 Anthropic 共同思考这一问题，而不是袖手旁观。我们能够在架构层面，而不仅仅是在政策层面，共同致力于新的安全和隐私功能。二十多年来，我们的客户一直信任我们将数据交给我们。正是基于这种经验，我们希望与 Anthropic 共同思考这一问题，而不是袖手旁观。我们能够在架构层面，而不仅仅是在政策层面，共同致力于新的安全和隐私功能。Meir Amiel，总裁、首席信任与基础设施官
Our clients want to put frontier models to work, and their security teams want the data to stay in infrastructure they control. Anthropic built Enterprise Frontier Safeguards with more than a hundred enterprises to do exactly that.我们的客户希望利用前沿模型，而他们的安全团队希望数据保留在他们控制的基础设施中。Anthropic 与一百多家企业共同构建了企业前沿安全防护（EFS），以实现这一目标。服务合伙人 Lan Guan，首席 AI 与数据官
Service Partner我们的客户希望利用前沿模型，而他们的安全团队希望数据保留在他们控制的基础设施中。Anthropic 与一百多家企业共同构建了企业前沿安全防护（EFS），以实现这一目标。服务合伙人
As AI models take on more regulated, sensitive workloads, scaling responsibly also comes down to architecture, not just policy commitments. Direct control over the data environment, paired with pattern-based automated safety monitoring, gives enterprises the concrete, structural capabilities they need to deploy with real oversight, accountability, and confidence.随着 AI 模型承担更多受监管的敏感工作负载，负责任地扩展也取决于架构，而不仅仅是政策承诺。对数据环境的直接控制，加上基于模式的自动化安全监控，为企业提供了部署所需的具体结构化能力，从而实现真正的监督、问责和信心。服务合伙人 Adnan Amjad，美国网络安全主管
Service Partner随着 AI 模型承担更多受监管的敏感工作负载，负责任地扩展也取决于架构，而不仅仅是政策承诺。对数据环境的直接控制，加上基于模式的自动化安全监控，为企业提供了部署所需的具体结构化能力，从而实现真正的监督、问责和信心。服务合伙人
The safeguards and the design of them—clearly, you heard our feedback. They put us in the driver's seat. The logs are under our control; they don't go anywhere else unless we want them to. It gives us control of the data, control of the information, and control of what's done after something that might exceed a safeguard is detected.这些安全防护措施及其设计——显然，你们听取了我们的反馈。它们让我们掌握了主动权。日志由我们控制；除非我们愿意，否则它们不会流向任何其他地方。这使我们能够控制数据、控制信息，并控制在检测到可能超出安全防护范围的情况后采取的措施。这些安全防护措施及其设计——显然，你们听取了我们的反馈。它们让我们掌握了主动权。日志由我们控制；除非我们愿意，否则它们不会流向任何其他地方。这使我们能够控制数据、控制信息，并控制在检测到可能超出安全防护范围的情况后采取的措施。Philip Martin，首席信息安全官
As AI becomes more embedded across the enterprise, security and trust are what move organizations from experimentation to deployment at scale. Enterprise Frontier Safeguards will build those in from the start: monitoring data stays in infrastructure the customer controls, and their own team decides who can access it.随着 AI 越来越深入企业，安全与信任是推动组织从实验转向大规模部署的关键。企业前沿安全防护（EFS）从一开始就内置了这些功能：监控数据保留在客户控制的基础设施中，并由他们自己的团队决定谁可以访问。服务合伙人 Morgan Adamski，美国网络安全、数据与技术主管
Service Partner随着 AI 越来越深入企业，安全与信任是推动组织从实验转向大规模部署的关键。企业前沿安全防护（EFS）从一开始就内置了这些功能：监控数据保留在客户控制的基础设施中，并由他们自己的团队决定谁可以访问。服务合伙人
Keeping customer data confidential is a promise Snowflake makes to every customer. We've always moved fast getting frontier models into their hands. The hard part was doing that safely under the strictest data guarantees. We partnered with Anthropic to design Enterprise Frontier Safeguards so we can do both: data stays in the customer's environment, under keys they control, running Anthropic's most capable models from day one. This is what responsible frontier AI looks like when it's built with platforms in mind.保持客户数据机密是 Snowflake 对每一位客户的承诺。我们一直致力于快速将前沿模型交到他们手中。难点在于如何在最严格的数据保障下安全地做到这一点。我们与 Anthropic 合作设计了企业前沿安全防护（EFS），以便我们能够两者兼顾：数据保留在客户环境中，使用他们控制的密钥，并从第一天起就运行 Anthropic 最强大的模型。这就是负责任的前沿 AI 在以平台为核心构建时的样子。保持客户数据机密是 Snowflake 对每一位客户的承诺。我们一直致力于快速将前沿模型交到他们手中。难点在于如何在最严格的数据保障下安全地做到这一点。我们与 Anthropic 合作设计了企业前沿安全防护（EFS），以便我们能够两者兼顾：数据保留在客户环境中，使用他们控制的密钥，并从第一天起就运行 Anthropic 最强大的模型。这就是负责任的前沿 AI 在以平台为核心构建时的样子。Mayank Upadhyay，首席安全与信任官
At Stripe, protecting customer data is foundational to how we operate. Anthropic’s Enterprise Frontier Safeguards will enable us to use covered frontier models while retaining conversation logs in Stripe’s AWS environment, with access and review governed by Stripe’s security controls.在 Stripe，保护客户数据是我们运营的基础。Anthropic 的企业前沿安全防护（EFS）将使我们能够使用相关前沿模型，同时将对话日志保留在 Stripe 的 AWS 环境中，并由 Stripe 的安全控制措施来管理访问和审查。在 Stripe，保护客户数据是我们运营的基础。Anthropic 的企业前沿安全防护（EFS）将使我们能够使用相关前沿模型，同时将对话日志保留在 Stripe 的 AWS 环境中，并由 Stripe 的安全控制措施来管理访问和审查。Matthew Kemelhar，安全主管
Rogo’s customers expect access to the best intelligence available, but never at the expense of security and guardrails around their data. Enterprise Frontier Safeguards will bring the most capable models to financial institutions while meeting the institutional-grade data requirements they demand. That combination of frontier intelligence and enterprise-grade controls is critical to deploying AI across financial services.Rogo 的客户期望获得现有的最佳情报，但绝不能以牺牲数据安全和护栏为代价。企业前沿安全防护（EFS）将为金融机构带来最强大的模型，同时满足他们要求的机构级数据要求。前沿智能与企业级控制的结合对于在金融服务领域部署 AI 至关重要。Rogo 的客户期望获得现有的最佳情报，但绝不能以牺牲数据安全和护栏为代价。企业前沿安全防护（EFS）将为金融机构带来最强大的模型，同时满足他们要求的机构级数据要求。前沿智能与企业级控制的结合对于在金融服务领域部署 AI 至关重要。Strib Walker，产品主管
FIS powers the infrastructure behind how money moves and how financial institutions operate, so any AI safeguard we deploy has to meet that scale and standard of trust. Our partnership with Anthropic already includes testing their most advanced frontier models against our own systems through Project Glasswing. Claude Enterprise Frontier Safeguards expands that work, keeping retained data in our own account and routing flags directly to our security team.FIS 为资金流动和金融机构运营提供基础设施支持，因此我们部署的任何 AI 安全防护措施都必须达到这一规模和信任标准。我们与 Anthropic 的合作已经包括通过 Project Glasswing 在我们自己的系统上测试他们最先进的前沿模型。Claude 企业前沿安全防护（EFS）扩展了这项工作，将留存的数据保留在我们自己的账户中，并将标记直接路由到我们的安全团队。FIS 为资金流动和金融机构运营提供基础设施支持，因此我们部署的任何 AI 安全防护措施都必须达到这一规模和信任标准。我们与 Anthropic 的合作已经包括通过 Project Glasswing 在我们自己的系统上测试他们最先进的前沿模型。Claude 企业前沿安全防护（EFS）扩展了这项工作，将留存的数据保留在我们自己的账户中，并将标记直接路由到我们的安全团队。Greg Barnett，首席信息安全官
Companies trust Cognition's autonomous engineers with real production work, and that trust depends on their work staying private. With Enterprise Frontier Safeguards, customer data and identities never leave our side. It will let us bring frontier AI to production work, no privacy tradeoff required.各公司信任 Cognition 的自主工程师来处理真实的生产工作，而这种信任取决于他们的工作是否保持私密。有了企业前沿安全防护（EFS），客户数据和身份永远不会离开我们。它将使我们能够将前沿 AI 带入生产工作，无需在隐私上做出妥协。各公司信任 Cognition 的自主工程师来处理真实的生产工作，而这种信任取决于他们的工作是否保持私密。有了企业前沿安全防护（EFS），客户数据和身份永远不会离开我们。它将使我们能够将前沿 AI 带入生产工作，无需在隐私上做出妥协。Scott Wu，首席执行官
Our customers' code and data are some of their most valuable intellectual property. Protecting that information is foundational to how we build at Factory. Together with Anthropic, we're enabling customers to use Claude's most capable models while keeping control of proprietary data in their hands. Enterprise Frontier Safeguards gives enterprises access to frontier intelligence with the data protections their security teams require.客户的代码和数据是他们最有价值的知识产权之一。保护这些信息是我们 Factory 构建方式的基础。我们与 Anthropic 携手合作，使客户能够使用 Claude 最强大的模型，同时将专有数据的控制权掌握在自己手中。企业前沿安全防护（EFS）为企业提供了访问前沿智能的机会，并提供了其安全团队所需的数据保护。客户的代码和数据是他们最有价值的知识产权之一。保护这些信息是我们 Factory 构建方式的基础。我们与 Anthropic 携手合作，使客户能够使用 Claude 最强大的模型，同时将专有数据的控制权掌握在自己手中。企业前沿安全防护（EFS）为企业提供了访问前沿智能的机会，并提供了其安全团队所需的数据保护。Eno Reyes，联合创始人兼 CTO
We have always maintained an unwavering commitment to client confidentiality and security. The leading legal and professional teams we serve view these principles as nonnegotiable, and we hold ourselves to the same standard. Enterprise Frontier Safeguards reflects this commitment, enabling customers with the most rigorous confidentiality requirements access to frontier models without the model provider retaining their data.我们始终保持对客户机密性和安全性的坚定承诺。我们所服务的领先法律和专业团队将这些原则视为不可谈判的条件，我们也以同样的标准要求自己。企业前沿安全防护（EFS）反映了这一承诺，使具有最严格机密性要求的客户能够在模型提供商不保留其数据的情况下使用前沿模型。我们始终保持对客户机密性和安全性的坚定承诺。我们所服务的领先法律和专业团队将这些原则视为不可谈判的条件，我们也以同样的标准要求自己。企业前沿安全防护（EFS）反映了这一承诺，使具有最严格机密性要求的客户能够在模型提供商不保留其数据的情况下使用前沿模型。John LaBarre，首席法务官
How EFS worksEFS 的工作原理
These controls are designed to work the same way whether you access Claude directly from Anthropic or through a cloud partner. Customers on Amazon Web Services, Google Cloud, and Microsoft Azure will get equivalent controls, with their activity data stored in their own cloud account, in the environment they already trust. We’re also working to support third-party offerings that serve customers that are eligible for Enterprise Frontier Safeguards.无论您是直接从 Anthropic 访问 Claude，还是通过云合作伙伴访问，这些控制措施的设计工作方式都是相同的。Amazon Web Services、Google Cloud 和 Microsoft Azure 的客户将获得同等的控制权，其活动数据将存储在他们自己的云账户中，即他们已经信任的环境中。我们也在努力支持那些为符合企业前沿安全防护（EFS）条件的客户提供服务的第三方产品。
Customer-owned storage, Customer-Managed Encryption Keys, and fully automated review are each opt-in, so you enable the ones your organization needs. None of them change model behavior, API pricing, or rate limits.客户拥有的存储、客户管理的加密密钥和完全自动化的审查均可选择加入，因此您可以启用组织所需的那些功能。它们都不会改变模型行为、API 定价或速率限制。
Anthropic doesn’t charge for Enterprise Frontier Safeguards. If customers elect to store their data in their cloud account, their cloud provider bills them for that storage, as well as reads, writes, and data egress fees, the same way it bills any other resource.Anthropic 不会对企业前沿安全防护（EFS）收费。如果客户选择将其数据存储在自己的云账户中，他们的云提供商会像计费任何其他资源一样，向他们收取存储费用以及读取、写入和数据流出费用。
Getting started入门指南
Enterprise Frontier Safeguards will roll out to customers in phases, with the goal of making it broadly available later this fall. To request access to Enterprise Frontier Safeguards, please complete this form.企业前沿安全防护（EFS）将分阶段向客户推出，目标是在今年秋季晚些时候广泛提供。如需申请使用企业前沿安全防护（EFS），请填写此表单。
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