01 / THE SIGNAL

我们发现了什么

Launch HN:Consus(YC F24)——为处理敏感数据的公司打造的 LLM 网关。我们将所有 AI 请求路由到符合 ITAR 出口管制及受控非密信息(CUI)要求的基础设施。

  • 来源:Hacker News(发现于 2026-10-14)
  • 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
  • 商业模式:API / Usage-based
  • 主题:独立产品
  • 初筛评分:23.9/100 · 收录 1 次
#独立开发#待验证#产品发现
02 / SOURCE & EVIDENCE

证据,比故事更重要。

发现产品或需求信号,暂未获得可核验的商业证据。

规则清洗与初筛,未经人工商业核验。原文语境、实际客户和付费情况仍需自行验证。

引用与数字披露

来源类型(原作者自述/第三方测算/媒体转引)需采集端标注,本版尚未落字段。

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中文辅助译文(全文)

Hacker News 大家好!我是 Eric,Consus 的创始人。我们将所有 AI 请求路由到符合 ITAR(《国际武器贸易条例》)出口管制和受控非密信息 (CUI) 要求的基础设施。Consus 自身满足 ITAR 的限制,并且我们最近针对 410 项 FedRAMP High 控制项完成了 FedRAMP 等效性审计。FedRAMP High 是美国政府针对处理敏感非密数据的云服务所制定的最严格安全基线。一旦此类数据发生泄露,可能造成严重或灾难性的危害。在处理 CUI 信息之前,必须先取得 FedRAMP 等效性认证(即授权)。演示地址:https://youtu.be/6MYxJe6P4oY 航空航天与国防行业正在经历快速增长。遗憾的是,由于必要的数据保护和合规风险,大多数公司难以使用 AI。这些公司如果能够使用其他行业习以为常的 AI 工具,就能发展得更快。在创立 Consus 之前,我的大部分职业经历都在航空航天与国防领域。我曾在 SpaceX 发射国家安全载荷,也是 Castelion 的早期员工。我亲眼目睹了合规层面的繁文缛节如何让企业难以采用新技术,并难以信任那些会接触其敏感数据的供应商。举个例子,我曾与一家卫星制造商合作,他们禁止使用任何 AI 工具,即便是非敏感工作也不行。尽管过去 9 到 12 个月内 AI 已经变得极为实用,但我仍然惊讶于有那么多航空航天与国防公司拒绝接触 AI。他们看得到 AI 的价值,但却担心模型提供商会用他们的数据进行训练、违反 ITAR 规则,或因未通过网络安全评估而丢掉新订单。这些担忧都合情合理。

有多种方式可以部分或全部解决这些问题,但我们选择聚焦于构建一个合规的 AI 推理层,它能够“即插即用”地接入任何 AI 工具或工作流。正如 OpenRouter 能与大多数工具集成一样,Consus 可以连接 ChatGPT、Claude 等工具,Pi 编程助手、Open WebUI 等开源工具,或与企业自行构建和维护的应用进行集成。几乎没有任何一家航空航天与国防公司同时驻扎在三大政府云(AWS、Azure、Google)之中。当我梳理前沿模型在合规条件下可以合法运行的位置以用于 ITAR 和 CUI 相关工作时,我发现每个提供商都只拥有模型的一个子集,每个模型也只达到了不同级别的合规程度。我们的客户并不按云提供商来思考问题,他们考虑的是所需的数据管控措施以及希望使用的模型。正因如此,我们构建了合规后缀(compliance suffix)。在底层,每个请求都会命中一个兼容 OpenAI API 的单一端点,在请求触及推理之前,系统会先对密钥进行验证并执行策略强制。每一个模型名称都必须携带合规后缀,例如 gpt-5.6-sol:fedramp-high 或 claude-opus-5-5:itar,任何不携带后缀的裸模型名称都会被直接拒绝。我们从不代理到标准的商用端点。我们的客户还可以构建模型允许列表,并为组织内的单个用户设置支出限额和模型使用限制。这些均通过我们的 Consus Portal 进行管理,团队可以在此管理支出、密钥和策略。我们经常听到的一个典型问题是:为什么不直接使用 AWS GovCloud 中的 Bedrock 或 Azure Government?

对于小型团队来说,仅是获取这些平台的使用权限就已经很困难。对于更大型的组织而言,政府云能让您继承所需的部分(但非全部)敏感数据处理控制。此外,模型分散在不同的提供商之间:GPT-5.6 Sol 仅在 Azure Government 中可用,而 Claude Opus 5.5 则通过 AWS GovCloud 中的 Bedrock 提供服务。如果您想同时使用两者,就必须搭建并加固两个独立的政府云环境。我们将所有这些模型统一收敛在一个端点之后,客户无需选择云厂商,而我们也为每一个云完成了相应的合规工作。考虑到数据的敏感性,Consus 不会持久化存储任何客户数据。所有提示词和回复内容只在请求处理期间保留在内存中,绝不进行日志记录或写入磁盘。零数据保留策略在我们自身以及基础设施/模型提供商那里都被严格执行。我们仅保留每一次请求和响应的元数据,用于计费和审计用途。Consus 在设计上不支持自助开通。ITAR 要求我们必须准确知晓每一把密钥背后的使用者,因此我们在签发 API 密钥之前会对每一家组织进行核实并签订合同。我们向客户收取的合规费起价为每月 40 美元/席位,AI 算力 token 按成本价计费。我们目前正在积极服务客户,诚挚欢迎任何来自安全专家或在强监管行业工作的开发者/工程师的反馈!参考链接: API 文档:https://gateway.consus.io/overview 安全与架构:https://gateway.consus.io/security 合规详情:https://consus.io/compliance

译文由上游机器翻译生成,可能有误;判断请以英文原文为准。

英文原文(来源本站未改写)

Hey Hacker News!I'm Eric, the founder of Consus.We route all AI requests to ITAR restricted and controlled unclassified information (CUI) compliant infrastructure.Consus itself satisfies ITAR restrictions, and we recently completed our FedRAMP equivalency audit against the 410 FedRAMP High controls.FedRAMP High is the U.S. government’s strictest security baseline for cloud services handling sensitive unclassified data.A breach of this data could cause severe or catastrophic harm.Achieving FedRAMP equivalency, or authorization, is required before processing CUI information.Demo: https://youtu.be/6MYxJe6P4oY Aerospace and defense is experiencing rapid growth.

Unfortunately, most companies are struggling to use AI because of necessary data protections & compliance risk.These companies can move even faster if they could use the AI tools that most other industries take for granted.I spent most of my career prior to Consus in aerospace & defense.I launched national security payloads at SpaceX, and was an early employee at Castelion.I’ve watched first hand how compliance red-tape makes it difficult for companies to adopt new technologies and trust vendors that touch their sensitive data.For example, I worked with a satellite manufacturer that doesn’t allow any AI tools, even for non-sensitive work.

Even as AI has become extremely useful over the past 9-12 months, I was surprised by how many aerospace & defense companies refused to touch it.They could see how it could be helpful, but they were scared about model providers training on their data, violating an ITAR rule, or risk losing new business because of a failed cyber assessment.These are all rational fears.There were a lot of ways to solve some/all of these problems, but we focused on building a compliant AI inference layer that can "plug" into any AI tool or workflow.

Just as OpenRouter integrates with most tools, Consus can connect to tools like ChatGPT or Claude, open source tools including the Pi coding agent or Open WebUI, or integrate with applications built and maintained by individual organizations.Almost no aerospace & defense company lives in all three major GovClouds (AWS, Azure, Google).When I mapped where frontier models can legally run for ITAR and CUI work, each provider had some subset of models, and each model achieved varying levels of compliance.Our customers don’t think in terms of cloud providers.They think about the data controls they require, and the model they want to use.That is why we built the compliance suffix.

Under the hood, every request hits a single OpenAI-compatible endpoint, where keys are verified and policy is enforced before anything touches inference.Every model name must carry a compliance suffix, such as gpt-5.6-sol:fedramp-high or claude-opus-5-5:itar, and any bare model name is rejected.We never proxy to the standard commercial endpoints.Our customers are also able to build an allowlist of models, and assign spend & model restrictions to individual users in the organization.This is all handled through our Consus Portal where teams can manage spend, keys, and policies.A typical question we hear is why not just use Bedrock in AWS GovCloud or Azure Government directly.

For small teams, just getting access to these platforms is difficult.For larger organizations, GovCloud lets you inherit some but not all of the controls needed to handle sensitive data.Also, models are split across providers: GPT-5.6 Sol is only available in Azure Government, while Claude Opus 5.5 is served through Bedrock in AWS GovCloud.If you want both, you are standing up and securing two separate government cloud environments.We run all of them behind one endpoint so customers don’t have to pick a cloud, and we handle the compliance work for each one.Given the data sensitivities, Consus does not store any customer data at rest.

All prompts and completions stay in memory only for the length of the request and are never logged or written to disk.Zero data retention is strictly enforced both on ourselves and the infrastructure/model providers.We do keep metadata on each request and response for billing and audit purposes.Consus is not self-serve by design.ITAR requires us to know exactly who is on the other end of every key, so we verify every organization and put a contract in place before issuing API keys.We charge our customers a compliance fee starting at $40/mo/seat plus AI tokens at cost.

We are actively serving customers, and would love any feedback from security experts, or developers/engineers working in highly regulated industries!References: API Documentation: https://gateway.consus.io/overview Security & Architecture: https://gateway.consus.io/security Compliance Details: https://consus.io/compliance

出处https://news.ycombinator.com/item?id=50073471抓取日期 · 采集源 Hacker News

03 / EVIDENCE GAPS

这条还缺什么证据?

下面每条都由本条已有字段推出(等级、理由、商业模式、来源次数、是否演示), 本站不生成推测性结论;通用验证方法放在方法论页。

  • 可核验的收入或付费证据查官网定价页与付费口径;第三方数据源(如 GetLatka)只作旁证,需标注来源与时点。
  • 只有单一来源找一手站点或其他渠道是否重复出现同一产品;社区热帖数量不等于商业进展。

通用验证清单(谁有这个问题/谁愿意付费/一个人能交付哪一小步)见我们的筛选方法。

04 / SIGNAL HISTORY

发现时间线